Railway station container scheduling optimization method, system, equipment and medium

Abstract

The invention discloses a railway station container scheduling optimization method, system, equipment and medium, and belongs to the technical field of railway station container scheduling, and the method comprises the steps: building a railway container yard container space assignment optimization model based on a container space freedom degree yard information representation method and a container stacking optimization process, stacking the to-be-stacked boxes by using a box stacking algorithm from a box yard to a train to obtain the optimal stacking positions of the to-be-stacked boxes; extracting the to-be-fetched box by using a box lifting algorithm from a train to a box yard to obtain an optimal target box position of the to-be-fetched box; using a heuristic algorithm to solve the railway container yard container quantity balanced distribution model to obtain the optimal division of the container area container quantity; and solving the railway container yard container space assignment optimization model by using a heuristic algorithm in combination with optimal division of container area container quantity to obtain an optimal container space assignment mode.

Description

Technical Field

[0001] The present invention belongs to the technical field of railway terminal container dispatching, and in particular relates to a railway terminal container dispatching optimization method, system, equipment and medium. Background Art

[0002] For the convenience of operation, when the space resources of railway container yards are relatively abundant, the yards generally adopt the method of stacking arriving and sending containers separately. The time when the sending container arrives at the yard is very uncertain. According to this feature, its site stacking strategy generally adopts the following two methods: one is to pre-arrange the containers before loading them on the departure train; the other is to sort and store the containers after they arrive. The advantage of the pre-arrangement strategy is that it simplifies the stacking work of the sending container yard and saves space in the yard. However, a large amount of pre-arrangement and moving work has increased the burden of the railway container center station. The advantage of the sorting and storage strategy is that it avoids a large amount of pre-arrangement work before the departure train, but a relatively complex management system and a large storage space are required in the sorting and storage process.

[0003] Arrival containers are opposite to outgoing containers. Arrival containers usually arrive at the railway container center station according to the operation plan. Based on this feature, a series of work such as loading and unloading, stacking, and extraction of arrival containers can be prepared in advance, so that the arrival containers can be picked up by the cargo owner as soon as possible, avoiding staying in the yard and occupying the storage resources of the container yard.

[0004] In recent years, with the rapid growth of demand for railway container transportation, some major international container yards have experienced explosive growth in their workload. Due to the limitation of yard area, many railway container centers have been unable to meet the actual operational needs by traditional methods of storing arriving and sending containers separately. Therefore, for some railway container centers with limited resources, mixed storage of arriving and sending containers is adopted to improve the utilization rate of yard space, provided that the yard area cannot be expanded. However, under this storage method, since there is no buffer zone, the arriving containers are directly placed in the yard container area. In addition, this storage method generally adopts a larger stacking height, which leads to an increase in the rate of container turnover and a decrease in the working efficiency of yard equipment. If the mixed stacking mode is adopted, the container yard information collection equipment and intelligent technical equipment must be fully configured to minimize the problems of container reversal and misloading, and give full play to the advantages of mixed stacking.

[0005] Separate storage of arriving and outgoing containers can effectively reduce the complexity of operations, reduce the rate of container turnover, and improve equipment utilization efficiency, but the utilization rate of the yard is relatively low, and this storage method is not suitable for yards with relatively tight space resources. On the contrary, the storage method of mixed stacking of arriving and outgoing containers has a relatively high utilization rate of container yards and is suitable for container yards with relatively tight space resources, but it puts forward higher requirements on the relevant supporting facilities and equipment and operation management technology of the container yard.

[0006] Intelligent management of container spaces in railway container areas is a systematic project. It not only includes the storage strategy of the yard, but also requires the cooperation of other facilities and equipment of the container terminal, such as railway gantries, highway gantries, loading and unloading equipment, etc. The intelligent management of railway container yards is also a closed-loop management system that integrates collection, decision-making, execution, and feedback, which is jointly built by the above hardware and intelligent management systems. Combined with intelligent technical equipment, after passing through the gantry, the vehicle / train will feed back its vehicle number, container number, transportation demand and other information to the management platform. After the platform calculates and decides the operation plan, it will be executed by the intelligent loading and unloading equipment, and the execution results will be fed back to the management platform.

[0007] The intelligent management of railway container yards should be combined with intelligent technology and equipment to realize the transformation of the yard from manual input to automatic machine recognition, and from manual experience judgment to system intelligent decision-making. However, there are problems such as low efficiency, wrong loading, missing loading, and container pressure and overturning caused by manual operations in the intelligent management of railway container yards. Summary of the invention

[0008] The purpose of the present invention is to overcome the problems of low efficiency, wrong loading, missing loading and container pressure and overturning caused by manual operations in the intelligent management of railway container yards, and propose a railway terminal container scheduling optimization method, system, equipment and medium.

[0009] In order to achieve the above object, the present invention adopts the following technical scheme: In a first aspect, the present invention provides a method for optimizing container dispatching in a railway terminal, comprising the following steps: A railway container yard slot assignment optimization model is constructed based on a yard information representation method of the slot freedom and a container stacking optimization process, wherein the constraint conditions of the railway container yard slot assignment optimization model are configured according to the container yard storage rules and the container stacking form, and the container yard storage rules and the container stacking form are preset according to the container attributes; Combined with the optimization model of container yard slot assignment, the algorithm for stacking containers from the container yard to the train and the algorithm for picking up containers from the train to the container yard are obtained; the algorithm for stacking containers from the container yard to the train is used to stack the containers to be stacked to obtain the optimal stacking position, and the algorithm for picking up containers from the train to the container yard is used to extract the optimal target position for the containers to be picked up; According to the container types of yard classification and storage space resource optimization, a balanced allocation model of railway container yard container quantity is constructed. The heuristic algorithm is used to solve the balanced allocation model of railway container yard container quantity to obtain the optimal division of container quantity in container area. Combined with the optimal division of container quantity in container area, the heuristic algorithm is used to solve the railway container yard slot assignment optimization model to obtain the optimal slot assignment method.

[0010] Furthermore, the container yard storage rules include: Before the yard floor is filled, all containers are free containers and are stacked on top first. When the bottom layer of the yard is full, the remaining containers will be stacked in the order of increasing number of stacks in the yard. The target location of loading and unloading boxes and the equipment moving path are within the equipment operation area; 20-foot containers and 40-foot containers are stacked on different levels, and no containers are stacked on top of non-compressible containers; Obtain the target location of the container to be stacked or picked up within the spatial range of the yard; The container stacking forms include vertical, flat and stepped types, and the containers are stacked and retrieved by multiple operations one by one.

[0011] Furthermore, the container stacking optimization process includes: In the first stage, when the bottom layer of the yard is not full and there is some remaining space in the yard, containers of the same attributes are stacked together according to the principle of top priority; In the second stage, when the attributes of the newly entered container are different from those of the containers on the yard, the newly entered container is placed in the space where the container with the same attributes can be placed; When there is no new container with the same attributes in the yard, or the attributes of the new container are different from those of all the containers in the yard, a container pressing operation is generated; the position or position set where the new container can be placed is obtained by maximizing the total freedom of the positions of the containers in the yard; In the third stage, when the yard can no longer meet the needs of single-load containers, double-load containers are generated, and the maximum limit on the freedom of container positions on the yard is used to obtain the position where containers can be stacked or retrieved; If the stacking status on the yard during the container picking operation returns to the previous stage, the next stacking or picking operation will be carried out according to the previous stage; The degrees of freedom of the container position are:

[0012] in, x ∈X, y ∈Y,(x , y )∈S, S∈X×Y, X represents the set range of positive integer horizontal coordinates of the box in the bottom projection coordinates, Y represents the set range of positive integer vertical coordinates of the box in the bottom projection coordinates, ( x , y ) is the bottom projection coordinate of the box, z is the container stacking height; S1 means that there is a container placed in the container space and it is not pressed by other containers, but the stack is not stacked to the highest level. f =1; S2 means that there is a box placed in the container position, but it is pressed by other boxes and is not in a stack of boxes with the same attributes, and the stack is not stacked to the highest position. The degree of freedom of the container position is k times the degree of freedom of the container position pressing it. S3 means that there is no box placed in the box position, and there are boxes stacked below it or there is a temporary detention mark at this position. The freedom degree of the box position is f =0; S4 means that there is a box placed in the box position, and it is in a stack with the same attributes, and the stack has been stacked to the highest level. f =2; S5 means that there are no containers stacked above or below the container space. f =3; When the adjacent containers stacked on the container are of the same attributes, k = α , α ∈[0,1] or k = β , β ∈[0,1], β < α ; The objective function of the railway container yard slot assignment optimization model is:

[0013] Among them, maxZ is the objective function of the optimization model for the assignment of container slots in the railway container yard, indicating that the sum of the degrees of freedom of all the container slots in the container yard is the highest; e Represents a 0-1 variable, 1 means loading a container from a train to a container yard, 0 means picking up a container from a container yard to a train, f represents the degrees of freedom of the container position, p (y) is a decision variable, which indicates the output code box position or box position; q ( d ) is the box area d The box location set; D is the set of all box cells,d ∈D; h ( y ) is a 0-1 variable, indicating whether the container is a container of a certain attribute. If yes, the value is 1, otherwise, the value is 0; g ( R ( d ), y ) is the box area d Middle box position y about R ( d ), R ( d ) is the box area d The stacking order and box location y The stacking order is based on the vertical stacking rule, starting from the smallest element, and taking the values ​​in turn. g ( R ( d ), y )=1,2,3,…, n ; L (y) is a temporary detention mark constraint; The constraints of the railway container yard slot assignment optimization model are as follows:

[0014] m 2> m 1>0

[0015] in, L (y) indicates that empty spaces without temporary detention marks shall be given priority when stacking containers. m 1 means there is a temporary detention sign when loading the box. m 2 means there is no temporary detention mark when stacking the box; h ( b ) indicates box b The generalized properties of h (p( y) ) represents the generalized classification attribute of the bin; The broad classification attribute is a set of classification attributes of two aspects: large box area and small box area; the large box area includes sending box area, arriving box area, international box area, refrigerated box area, special box area, empty box area, spare box area, maintenance box area, cleaning and disinfection box area; each large box area is divided into several small box areas according to the classification attributes and previous cargo flows; vertical stacking is adopted when stacking in the small box areas.

[0016] Furthermore, the container loading algorithm from the container yard to the train includes the following steps: S11, input the box attributes of the waiting box, and determine the box cell to which the waiting box belongs; S12, in the found box area, search from the minimum element to the maximum element according to the code-taking box sequence table of the box area, and remove the temporary detention mark for the empty box position with the temporary detention mark encountered during the search, until the first full box position is found, and mark the full box minimum element on the full box position; S13, according to the order table of the boxes in the box area, search from the minimum element to the maximum element step by step, find the first box position that can be used for box loading in the yard, and the box position has no temporary detention mark, and record the sum of the total freedom degrees of each box position in the new stacking state on the yard after the box to be stacked is stacked in the box position as the sum of the first degree of freedom. If all the box positions that can be used for box loading have temporary detention marks, go to S15; S14, according to the box picking sequence table of the box area code, search for empty box positions that can be used for stacking boxes without temporary detention marks one by one, and calculate the sum of the degrees of freedom of each box position on the stacking yard after placing the box to be stacked in the box position, and record it as the sum of the second degrees of freedom. If the sum of the second degrees of freedom is greater than the sum of the first degrees of freedom, the priority position of the stackable box is replaced with the current box position, otherwise it is retained as the original position as the priority stacking position, and go to S16; S15. If no available box position without a temporary detention mark is found in S12, all the box positions with temporary detention marks are found according to the box position sequence table, and the temporary detention marks on the box positions are removed, and then go to S13; S16, updating the freedom of the box positions in the operating box area in the yard; S17, output the coordinates of the box location that can be stacked, if not found, output no information; The algorithm for picking up boxes from a train to a box yard comprises the following steps: S21. Input the attributes of the box to be picked up and find the box cell to which the box to be picked up belongs, otherwise there is no solution information; S22, in the found container cell, search from the minimum element to the maximum element according to the container cell pick-up sequence table, find the first container with the same attributes as the container to be picked up and completely free without a temporary detention mark, and set a temporary detention mark on the container position for picking up the container. If no container that meets the conditions is found, go to S24; S23, updating the freedom of the box positions in the operating box area in the yard; S24: Output the coordinates of the box location found. If not found, output no information.

[0017] Furthermore, the container yard is classified into container areas, which include a dispatch container area, an arrival container area, an international container area, a customs supervision area, a refrigerated container area, a special container area, an empty container area, a spare container area, a maintenance container area, and a cleaning and disinfection container area; The container types for optimizing storage space resources include DX type of containers to be unloaded, DT type of containers to be picked up, DF type of containers to be dispatched, and DY type of containers to be transported; The DX type of container to be unloaded means that the container is still on the train, waiting to be unloaded and stored in the yard; The DT type of container to be picked up means that the container has been stacked in the yard and is waiting for the truck to enter the yard to pick up the container; The DF type of container to be dispatched indicates a container to be dispatched that has not yet been allocated to the yard and is waiting to be transported to the yard by a container truck for storage; The DY type of waiting box indicates a sending box that is already in the yard waiting to be loaded onto a train.

[0018] Furthermore, the objective function of the railway container yard container quantity balanced allocation model is as follows:

[0019] Among them, w1 represents the weight coefficient of the container quantity balance of the container truck operation in the yard container area, w2 represents the weight coefficient of the container quantity balance of the train operation in the yard container area, and w3 represents the weight coefficient of the overall container quantity balance in the yard container area; express t Transported to container yard during the period and distributed to container area i The number of DF boxes loaded on the train, express t Unloading from train to container area during the period i The number of DX boxes taken away, express t The number of DT boxes picked up during the period, express t The number of DY-type containers loaded onto trains during the period, Indicates that the stack is in the box area i Zhongzai t The number of DY-type boxes loaded onto trains during this period, Indicates the number of DT boxes taken away. Indicates that the stack is in the box area i Zhongzai t The number of DT boxes taken away during the period; The constraints of the railway container yard container quantity balanced allocation model are as follows: t =1,2… T ; K =0,1… T - t t =1,2… T ; i =0,1… B , t =1,2… T ;K =0,1… T - t , t =1,2… T ; i =0,1… B , t =1,2… T ; i =0,1… B , t =1,2… T ; i =0,1… B

[0020] in, express t Transported to container yard during the period and distributed to container area i The quantity of DF type boxes, express t Transported to container yard during the period and distributed to container area i in t + k The number of DF boxes loaded on the train during the period, B Indicates the number of container areas in the yard. T Indicates the time periods contained in a planning cycle. express t Unloading from train to container area during the period i The quantity of DX boxes, express t Unloading from train to container area during the period i in t + k The number of DX boxes taken away during the period, Indicates that the stack is in the box area i Zhongzai t The number of DT boxes taken away during the period, Indicates that it has been allocated in the box area at the beginning of the planning period i in and t The number of DT boxes taken away during the period, Indicates t Unloading from train to container area during the period i in t - k The number of DX boxes taken away during the period, Indicates that the stack is in the box area iZhongzai t The number of DY-type boxes loaded onto trains during this period, Indicates that it has been allocated in the box area at the beginning of the planning period i in and t The number of DF boxes loaded onto trains during this period, express t Transported to container yard during the period and distributed to container area i in t - k The number of DF boxes loaded on the train during the period, express t Box area at the beginning of the period i The total number of boxes in Indicates box area i storage capacity.

[0021] Furthermore, the heuristic algorithm comprises the following steps: S31, initializing planning cycle parameters, setting time variable t=1, and inputting container information; S32, calculating the operation volume of DF containers in each container area in the yard during period t, dividing them into each container area according to the constraint conditions, and calculating the total operation volume of the four types of containers in the yard at present, and obtaining the operation volume ranking of each container area; S33, limiting the workload of each box area and distributing it to each box area in order from low to high, and judging whether it is finished; S34, calculating the total amount of the four types of containers in each period, and calculating and storing the objective function value; S35, judging whether there is a DX container in the container area with the largest workload, if yes, proceed to S36, otherwise proceed to S37; S36, determine whether the DX-type containers leaving the market during this period are allocated to this container area because the workload of this container area is the smallest during the allocation period. If yes, proceed to S38, otherwise return to S35; S37, determine whether there is DX-type container volume in the container area with the largest operation volume during the period, if not, proceed to S39, otherwise return to S35; S8, let t = t-1, determine whether the current period is the start period of the planning cycle, calculate the objective function value, and go to S39; S39. Compare the objective function values ​​of the two calculations and take the minimum value as the objective function of the model.

[0022] In a second aspect, the present invention provides a railway terminal container dispatching optimization system, comprising: Constructing a railway container yard slot assignment optimization model module, which is used to construct a railway container yard slot assignment optimization model based on the yard information representation method of the slot freedom degree and the container stacking optimization process, wherein the constraint conditions of the railway container yard slot assignment optimization model are configured according to the container yard storage rules and the container stacking form, and the container yard storage rules and the container stacking form are preset according to the container attributes; The module for obtaining the optimal stacking position of the boxes to be stacked and the optimal target box position for the boxes to be picked up is used to obtain the stacking algorithm from the container yard to the train and the box picking algorithm from the train to the container yard in combination with the railway container yard box position assignment optimization model; the optimal stacking position of the boxes to be stacked is obtained by stacking the boxes from the container yard to the train, and the optimal target box position of the boxes to be picked up is extracted by using the box picking algorithm from the train to the container yard; The module for obtaining the optimal slot assignment method is used to construct a balanced allocation model for railway container yard container quantities according to the yard classification and container types that optimize storage space resources. The heuristic algorithm is used to solve the balanced allocation model for railway container yard container quantities to obtain the optimal division of container quantities in the container area. Combined with the optimal division of container quantities in the container area, the heuristic algorithm is used to solve the railway container yard slot assignment optimization model to obtain the optimal slot assignment method.

[0023] In a third aspect, the present invention provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method for optimizing railway terminal container scheduling when executing the computer program.

[0024] In a fourth aspect, the present invention provides a computer-readable storage medium storing a computer program, and a method for optimizing railway terminal container scheduling when the computer program is executed by a processor.

[0025] Compared with the prior art, the present invention has the following beneficial technical effects: The present invention proposes a railway yard container scheduling optimization method, which can more reasonably utilize the yard space and avoid confusion and interference between containers of different attributes through preset container yard storage rules and container stacking forms; through the railway container yard box quantity balanced allocation model, it is ensured that the box quantity of each yard is evenly distributed to avoid the situation that some yards are overcrowded while other yards are idle; balanced box quantity allocation helps to maximize the overall storage capacity of the yard and improve space utilization; the yard box location assignment model further refines the specific storage location of the container in the yard according to the optimal division of the box quantity in the container area; through reasonable box location assignment, every inch of the yard space is fully utilized, the idle box locations are reduced, and the storage density of the yard is improved; balanced box quantity allocation and reasonable box location assignment help to reduce the number of container unloading in the yard; the reduction in the number of unloading can reduce operating costs and improve operating efficiency, and also help to reduce equipment wear and energy consumption; through Model optimization can form a more scientific and reasonable operation process; the optimized operation process helps to reduce the waiting time and idle time during the operation and improve the overall operation efficiency; for the mixed storage mode, the heuristic algorithm that adapts to large-scale complex scenarios is used to solve the model. The scheduling optimization method can reduce the waiting time of the equipment, avoid container reversal or reduce the number of container reversals to make the container stacking and extraction operations smooth, improve the utilization rate of equipment, and thus shorten the container transportation time. By optimizing the constraints in the model, conflicts and interferences between different operations can be avoided, the safety and reliability of the operation process can be ensured, the utilization rate of the yard can be improved, the operation efficiency can be improved, the operating costs can be reduced, the safety and reliability can be enhanced, the service capacity of the railway container yard and the quality of the container slot assignment decision-making can be improved, the operation process can be optimized, the management decision-making ability can be enhanced, and the problems of low efficiency, wrong loading, missing loading, and pressure and reversal of containers caused by manual operations in the intelligent management of railway container yards can be solved. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The drawings described herein are for explanation purposes only and are not intended to limit the scope of the present invention in any way. In addition, the shapes and proportional dimensions of the components in the drawings are only for illustration purposes to help understand the present invention, and are not intended to specifically limit the shapes and proportional dimensions of the components of the present invention. In the drawings: Figure 1 The present invention is a flow chart of a method for optimizing railway terminal container dispatching.

[0027] Figure 2 The present invention is a structural diagram of a railway terminal container dispatching optimization system.

[0028] Figure 3 This is an electronic equipment diagram of a railway terminal container scheduling optimization method of the present invention.

[0029] Figure 4This is a diagram for optimizing the storage plan for railway container yards.

[0030] Figure 5 This is a schematic diagram of the vertical box stacking sequence.

[0031] Figure 6 This is a schematic diagram of the flat-pack box stacking sequence.

[0032] Figure 7 This is a schematic diagram of the step-by-step box stacking sequence.

[0033] Figure 8 This is a schematic diagram of the bottom floor planning of the container yard.

[0034] Fig. 9 Schematic diagram of the freedom of container yard slots.

[0035] Fig.10 This is a thought process diagram for optimizing the storage resources in railway container yards.

[0036] Fig.11 Provides solutions for intelligent assignment of railway container slots. DETAILED DESCRIPTION

[0037] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0038] Embodiment 1 See also Figure 1 , a railway terminal container dispatching optimization method, comprising the following steps: A railway container yard slot assignment optimization model is constructed based on a yard information representation method of the slot freedom and a container stacking optimization process, wherein the constraint conditions of the railway container yard slot assignment optimization model are configured according to the container yard storage rules and the container stacking form, and the container yard storage rules and the container stacking form are preset according to the container attributes; Combined with the optimization model of container yard slot assignment, the algorithm for stacking containers from the container yard to the train and the algorithm for picking up containers from the train to the container yard are obtained; the algorithm for stacking containers from the container yard to the train is used to stack the containers to be stacked to obtain the optimal stacking position, and the algorithm for picking up containers from the train to the container yard is used to extract the optimal target position for the containers to be picked up; According to the container types of yard classification and storage space resource optimization, a balanced allocation model of railway container yard container quantity is constructed. The heuristic algorithm is used to solve the balanced allocation model of railway container yard container quantity to obtain the optimal division of container quantity in container area. Combined with the optimal division of container quantity in container area, the heuristic algorithm is used to solve the railway container yard slot assignment optimization model to obtain the optimal slot assignment method.

[0039] This embodiment improves the utilization rate of the yard by optimizing space allocation and reducing the number of container turnovers. Through the preset container yard rules and container stacking forms, the yard space can be used more reasonably to avoid confusion and interference between containers of different attributes. The container slot assignment optimization model can minimize the number of container turnovers and turnovers, thereby reducing the extra time and cost in the operation process. By shortening the transportation time and optimizing the operation process to improve the operation efficiency, the scheduling optimization method can reduce the waiting time of the equipment, improve the utilization rate of the equipment, and thus shorten the container transportation time; by constructing a railway container yard container slot assignment optimization model, a more efficient stacking and picking algorithm can be obtained, making the operation process smoother and more efficient. Safety and reliability are enhanced by avoiding operation conflicts and improving emergency response capabilities. By optimizing the constraints in the model, conflicts and interference between different operations can be avoided to ensure the safety and reliability of the operation process; in an emergency, the location of the required container can be quickly and accurately located to improve the speed and efficiency of emergency response. Through precise and balanced allocation of containers, efficient use of yard space is ensured, vacant areas are reduced, and storage capacity is maximized; the container allocation model further optimizes the specific storage location of containers, reduces space waste, and improves the overall operational efficiency of the yard; balanced container allocation helps to simplify loading and unloading operations, reduce the frequent movement of containers between different yards, and thus reduce operating costs and time; reasonable container allocation reduces the moving distance and waiting time of equipment such as cranes or forklifts, and improves loading and unloading efficiency; scheduling optimization methods provide scientific data support to help managers make more accurate and efficient decisions and optimize resource allocation.

[0040] Combined with intelligent technical equipment, the yard can be transformed from manual input to automatic machine recognition, and from manual experience judgment to system intelligent decision-making. The technical equipment mainly includes electronic tags, readers and other equipment related to data information collection and identification; RFID equipment related to container positioning in the yard; gantry cameras, sensors and other equipment related to vehicle / train entry and exit information collection, and wireless transmission equipment for data interaction in the yard. Through the above hardware equipment, combined with the intelligent optimization management method of container yard slots, the intelligent management of railway container yards can be realized, reducing the problems of low efficiency, wrong loading, missing loading, and container pressure and overturning caused by manual operations.

[0041] By analyzing the business characteristics of the container yard, its business can be summarized into five business scenarios: loading trains, unloading trains, loading cars, unloading cars, and intra-yard movement. Further combined with facilities such as yards, tracks, and roads, the business scenarios can be summarized into three categories: truck / train - container yard, container yard - truck / train, and container yard - container yard.

[0042] For the container truck / train-container yard, when a heavy container truck or heavy vehicle enters the container yard through the gate, that is, when the container is stored from the outside to the yard, the gate will transmit the license plate number, vehicle number, sequence number, container number and other information to the intelligent management platform. For the yard with gantry crane as the main loading and unloading equipment, attention should be paid to balancing the workload of the area responsible for each gantry crane to make full use of the storage space and improve the efficiency of loading and unloading operations. At the same time, attention should be paid to the relationship between container attributes, and the freedom of container space should be optimized as much as possible to reduce the operation of container reversal due to container compression.

[0043] For the container yard - truck / train, when an empty truck or empty vehicle enters the container yard to pick up containers, that is, when containers are loaded and unloaded from the yard to the outside, because the balanced operation of each gantry crane and the consistency of container attributes have been considered when the containers are stored, when formulating the loading plan, the focus should be on maximizing the loading and unloading efficiency. Therefore, when loading and unloading containers from the container yard to the truck / train, the essential problem becomes the generalized shortest path problem of containers or loading and unloading equipment, so as to reduce operating costs and improve efficiency.

[0044] For container yard to container yard, when the container yard needs to be moved within the container yard due to inventory or compression, it is also necessary to consider the balance of operations of various loading and unloading equipment in the yard, and when formulating the moving plan, it is necessary to consider the impact of container attributes on container space.

[0045] In summary, the optimization ideas for railway container yard storage plan are as follows: Figure 4 shown.

[0046] The basic rules of the intelligent dispatch optimization method are to clearly define the information of each container and container slot. First, the relevant operation scenarios and slot characteristics are defined according to the container attributes, and then the container yard storage rules are formulated to further optimize the container assignment plan. The basic definitions are as follows: Attribute box: The internal freight handler determines the attribute A as the main attribute feature of the container based on the attribute features of the container in the container yard, such as the owner unit, destination name, type of packed goods, size, etc. This type of container is called attribute box A.

[0047] Stacking refers to a three-dimensional space in a container yard where there is only one container on the bottom layer and other containers are stacked vertically on top of it to a certain height.

[0048] Container stacking operation, in the model, refers to the operation of stacking different containers together.

[0049] A free box is a box that is not suppressed by other classification attribute boxes.

[0050] A semi-free box refers to a box that is suppressed by other classification attribute boxes but has the same classification attributes.

[0051] A non-free box refers to a box that is suppressed by other classification attribute boxes and there is no free box with the same classification attribute.

[0052] Degree of freedom refers to the degree of freedom of a certain container position in the yard. The degree of freedom will be different due to different characteristics of the container position.

[0053] The principle of top priority means that during the container stacking operation, containers of the same attribute will be stacked on the same stack first, and as close as possible to the maximum number of stacking layers allowed by the yard. When the maximum number of stacking layers is reached, if there are still containers of the same attribute remaining, they will be stacked on another stack according to the same principle until all containers of that attribute are stacked. The final effect is that containers of the same attribute are stacked together and occupy the least area on the bottom floor of the yard.

[0054] A single-layered container refers to two containers of different attributes stacked in the same column of the stack; a double-layered container refers to three containers of different attributes stacked in the same column, and so on.

[0055] Furthermore, container yard storage rules include: Before the yard floor is filled, all containers are free containers and are stacked on top first. When the bottom layer of the yard is full, the remaining containers will be stacked in the order of increasing number of stacks in the yard. The target location of loading and unloading boxes and the equipment moving path are within the equipment operation area; 20-foot containers and 40-foot containers are stacked on different levels, and no containers are stacked on top of non-compressible containers; Obtain the target location of the container to be stacked or picked up within the spatial range of the yard; See also Figure 5 , Figure 6 , Figure 7 , container stacking forms include vertical, flat and stepped, and containers are stacked and retrieved one by one in multiple operations. In actual container retrieval operations, no matter whether the customer needs one or more containers, the demand can be converted into multiple one-time container pickup demands, that is, stacking and retrieval are done one by one, which is regarded as multiple operations of a single container.

[0056] When a container pressing operation is inevitable, the containers are stacked in the order of increasing number of containers pressed in each stack in the yard during the operation. That is, only when each stack in the yard has already generated a heavy container and there is no free space to meet the heavy container pressing, a new number of containers will be generated, so that the number of containers pressed will increase. The space of the yard must be able to meet the stacking space needs of the containers that the yard is responsible for. Therefore, the target location of the container to be stacked or extracted cannot exceed the space range of the yard.

[0057] Furthermore, the container stacking optimization process includes: In the first stage, when the bottom layer of the yard is not full and there is some remaining space on the yard, containers of the same attributes are stacked together according to the principle of top priority, so that as many containers as possible can be stacked on the yard to improve the utilization rate of the yard; In the second stage, when the attributes of the newly entered container are different from those of the containers on the yard, the newly entered container is placed in the space where the container with the same attributes can be placed; When there is no new container with the same attributes in the yard, or the attributes of the new container are different from those of all the containers in the yard, a container pressing operation is generated; the position or position set where the new container can be placed is obtained by maximizing the total freedom of the positions of the containers in the yard; As containers with different attributes are stacked in the yard, they occupy the bottom space of the yard. When the attributes of the newly entered container are different from those of the containers on the yard, the new container will be placed in the space where the container with the attribute can be placed; when there is no position for the container with the same attribute or the attributes of the new container are different from all the attributes on the yard, a container pressing operation will be generated. By defining the freedom of the container position in the yard, considering the impact of the stacking and picking operations on each degree of freedom, the total freedom of the position of the containers on the yard is maximized, so as to obtain the position or position set where the new container can be placed; In the third stage, when the yard can no longer accommodate a single-load container, a double-load container is generated, and the maximum degree of freedom of the container position on the yard is used to constrain the position where the container can be stacked or retrieved; similar to the second stage, the maximum degree of freedom of the container position on the yard is used to constrain the position where the container can be stacked or retrieved; If the stacking state on the yard returns to the state of the previous stage during the container picking operation, the next stacking or extraction operation will be carried out according to the previous stage; when at a certain stage, due to the influence of the container picking operation, such as a large number of containers picked up in a batch, the stacking state on the yard may return to a stage before this stage, then the operation will be carried out according to the converted state stage. Due to the influence of the container picking operation, the stacking state of the container yard with a heavy container in the second stage is converted to the stacking state without a heavy container in the first stage, then the next stacking or extraction operation will be carried out according to the first stage.

[0058] For a given yard, the bottom area that can be used to stack containers is determined, and the highest number of stacking layers C in the yard can be determined by factors such as the degree of ground hardening and the type and operating capacity of loading and unloading machinery. When a container in the yard is stacked to a certain height, the number of stacking layers is represented by a positive integer Z, Z∈[1,C]. The schematic diagram of the bottom container space planning of the container yard is shown in Figure 8 As shown. It can be seen that in reality, the storage yard can be regular or irregular. The digital coordinates in each grid in the figure represent the projection of the container position on the bottom plane. Through the division of the bottom container positions of the storage yard and the representation of the plane coordinates of each container position, for a certain storage yard, X represents the set range of positive integer horizontal coordinates of the container position in the bottom projection coordinates, and Y represents the set range of positive integer vertical coordinates of the container position in the bottom projection coordinates. X×Y represents the Cartesian product of the elements in the two sets X and Y, then the bottom projection coordinates of a certain container position ( x , y ) takes a value of x ∈X, y ∈Y,( x , y )∈S, S∈X×Y, further through the container storage height z The specific location of the container in the yard can be determined, and the definition p(a) Indicates container a The position function, f represents the degree of freedom of the container position. For any container position in the yard, the following relationship exists: The degrees of freedom of the container position are:

[0059] in, x ∈X, y ∈Y,( x , y )∈S, S∈X×Y, X represents the set range of positive integer horizontal coordinates of the box in the bottom projection coordinates, Y represents the set range of positive integer vertical coordinates of the box in the bottom projection coordinates, ( x , y ) is the bottom projection coordinate of the box, z is the container stacking height; S1 means that there is a container placed in the container space and it is not pressed by other containers, but the stack is not stacked to the highest level. f =1; S2 means that there is a box placed in the container position, but it is pressed by other boxes and is not in a stack of boxes with the same attributes, and the stack is not stacked to the highest position. The degree of freedom of the container position is k times the degree of freedom of the container position pressing it. S3 means that there is no box placed in the box position, and there are boxes stacked below it or there is a temporary detention mark at this position. The freedom degree of the box position is f =0; S4 means that there is a box placed in the box position, and it is in a stack with the same attributes, and the stack has been stacked to the highest level. f =2; S5 means that there are no containers stacked above or below the container space. f =3; When the adjacent containers stacked on the container are of the same attributes, k = α , α ∈[0,1] or k = β , β ∈[0,1], β < α ; In defining the degrees of freedom, it is defined for each bin. For bins ( x , y , z ) is the spatial position of a box in the box area. At this time, the classification attribute set of the box area and the box area is called the generalized classification attribute. h ( a ) indicates box a The generalized properties of h (p( a) ) represents the generalized classification attribute of the box location. While considering the box partition, in order to avoid multiple optimal solutions at the same time, vertical stacking is adopted when stacking in the box area.

[0060] In order to better explain the degrees of freedom, the degrees of freedom in the definition are defined based on each box area, that is, the degrees of freedom involved in the definition ( x , y , z ) is a slot in a certain container area. The following example illustrates the degrees of freedom of some slots. In the six sub-graphs in the figure below, A and B represent two different attributes. Marking them on the top of the slots indicates that containers have been stacked there and have been assigned their respective attribute categories; unmarked slots indicate that they are empty slots. Based on the above definition of the degrees of freedom of container slots, the degrees of freedom of each slot can be obtained. The degrees of freedom of each slot in the figure have been marked on the slots, and some of the corresponding scenarios are listed, such as Fig. 9 shown.

[0061] In the yard operation, in order to ensure the principle of "first in, first out", a "temporary detention" mark is set for each container position. When stacking containers, empty containers without "temporary detention" marks are given priority. If no empty containers are found, empty containers with "temporary detention" marks are considered. Without violating the principle of "first in, first out", the freedom of container positions in the entire yard is maximized.

[0062] The objective function of the optimization model for railway container yard slot assignment is:

[0063] Among them, maxZ is the objective function of the optimization model for the assignment of container slots in the railway container yard, indicating that the sum of the degrees of freedom of all the container slots in the container yard is the highest; e Represents a 0-1 variable, 1 means loading a container from a train to a container yard, 0 means picking up a container from a container yard to a train, f represents the degrees of freedom of the container position, p (y) is a decision variable, which indicates the output code box position or box position; q ( d ) is the box area d The box location set; D is the set of all box cells, d ∈D; h ( y ) is a 0-1 variable, indicating whether the container is a container of a certain attribute. If yes, the value is 1, otherwise, the value is 0; g ( R ( d ), y ) is the box area d Middle box position y about R ( d ), R ( d ) is the box area d The stacking order and box location y The stacking order is based on the vertical stacking rule, starting from the smallest element, and taking the values ​​in turn. g ( R ( d ), y )=1,2,3,…, n ; L (y) is a temporary detention mark constraint; The constraints of the optimization model for railway container yard slot assignment are as follows:

[0064] m 2> m 1>0

[0065] in, L (y) indicates that empty spaces without temporary detention marks shall be given priority when stacking containers. m 1 means there is a temporary detention sign when loading the box. m 2 means there is no temporary detention mark when stacking the box; h ( b ) indicates box b The generalized properties of h (p( y) ) represents the generalized classification attribute of the bin; The broad classification attributes are a collection of classification attributes of two aspects: large container areas and small container areas. Large container areas include sending container areas, arriving container areas, international container areas, refrigerated container areas, special container areas, empty container areas, spare container areas, maintenance container areas, and cleaning and disinfection container areas. Each large container area is divided into several small container areas based on the classification attributes and previous cargo flows. Vertical stacking is used for stacking in small container areas.

[0066] After defining the degrees of freedom for each container position, the stacking or extraction of containers on the yard will directly affect the degrees of freedom of the original containers on the yard. When stacking, the degrees of freedom of the original container positions on the yard will be reduced, and the newly added containers will have more degrees of freedom; when extracting, the degrees of freedom of the original container positions on the yard will be increased, and there may be more and more cases where there are no containers on the stacking row. Therefore, the optimization goal of maximizing the overall freedom of the yard is achieved.

[0067] Combined with the railway container slot assignment optimization model, the container loading and unloading algorithms are designed for the two scenarios of “container yard - (train) car” and “(train) car - container yard” respectively.

[0068] Furthermore, the algorithm for loading containers from the container yard to the train includes the following steps: S11, input the box attributes of the waiting box, and determine the box cell to which the waiting box belongs; S12, in the found box area, search from the minimum element to the maximum element according to the code-taking box sequence table of the box area, and remove the temporary detention mark for the empty box position with the temporary detention mark encountered during the search, until the first full box position is found, and mark the full box minimum element on the full box position; S13, according to the order table of the boxes in the box area, search from the minimum element to the maximum element step by step, find the first box position that can be used for box loading in the yard, and the box position has no temporary detention mark, and record the sum of the total freedom degrees of each box position in the new stacking state on the yard after the box to be stacked is stacked in the box position as the sum of the first degree of freedom. If all the box positions that can be used for box loading have temporary detention marks, go to S15; S14, according to the box picking sequence table of the box area code, search for empty box positions that can be used for stacking boxes without temporary detention marks one by one, and calculate the sum of the degrees of freedom of each box position on the stacking yard after placing the box to be stacked in the box position, and record it as the sum of the second degrees of freedom. If the sum of the second degrees of freedom is greater than the sum of the first degrees of freedom, the priority position of the stackable box is replaced with the current box position, otherwise it is retained as the original position as the priority stacking position, and go to S16; S15. If no available box position without a temporary detention mark is found in S12, all the box positions with temporary detention marks are found according to the box position sequence table, and the temporary detention marks on the box positions are removed, and then go to S13; S16, updating the freedom of the box positions in the operating box area in the yard; S17, output the coordinates of the box location that can be stacked, if not found, output no information; In the actual application of container picking operations, if all the containers in a certain container area cannot be taken out for a long time, it may cause the containers near the minimum element to stay for too long, thus causing the "large container" problem. Although the same generalized classification attribute boxes are equivalent, if the sum of the entire degree of freedom in the yard is maximized, the container that has just been stacked will be extracted in the container picking operation, and the order of taking the containers is "last in, first out", which causes the previously stacked containers to stay in the yard for a long time, violating the "first in, first out" principle. In order to solve this problem, a 0-1 variable " e ", when it is a container picking operation, this item is 0, and the container that meets the conditions can be directly picked up according to the container picking sequence table of the container area.

[0069] The algorithm for separate stacking and picking up containers from the train to the container yard includes the following steps: S21. Input the attributes of the box to be picked up and find the box cell to which the box to be picked up belongs, otherwise there is no solution information; S22, in the found container cell, search from the minimum element to the maximum element according to the container cell pick-up sequence table, find the first container with the same attributes as the container to be picked up and completely free without a temporary detention mark, and set a temporary detention mark on the container position for picking up the container. If no container that meets the conditions is found, go to S24; S23, updating the freedom of the box positions in the operating box area in the yard; S24: Output the coordinates of the box location found. If not found, output no information.

[0070] If a location for picking up a container has been found in the yard, but the attributes of the container located at that location are inconsistent with the container to be picked up, it means that all the containers with the same attributes as the container to be picked up on the yard are pressed by containers with other attributes, or there are no containers with this attribute stacked on the yard. When a container with this attribute is pressed by containers with other attributes, the number of containers with other attributes pressing on this container is the least within the yard space. In this case, a container unloading operation will also be generated. When there are no containers with this attribute stacked on the yard, the direct output operation fails.

[0071] Furthermore, the yard is classified into container areas, which include the dispatching container area, arrival container area, international container area, customs supervision area, refrigerated container area, special container area, empty container area, spare container area, maintenance container area, and cleaning and disinfection container area; The container types for optimizing storage space resources include DX type for unloading, DT type for picking up, DF type for dispatching and DY type for transporting; DX type of container waiting to be unloaded means that the container is still on the train, waiting to be unloaded and stored in the yard; DT type means that the container has been stacked in the yard and is waiting for the truck to enter the yard to pick up the container; DF type of container to be dispatched indicates the container to be dispatched which has not been allocated to the yard and is waiting to be transported to the yard by a container truck for storage. The DY type of container waiting to be shipped indicates the container that is already in the yard waiting to be loaded onto the train.

[0072] In order to give full play to the overall efficiency of the yard logistics system, economical and practical loading and unloading machinery should be selected. In the railway container yard, the yard can be divided into a bulk cargo placement area and a scattered cargo placement area, and then the container area, container space and on-site roads can be reasonably divided according to the operation process to minimize cross-interference of operations.

[0073] The empty container storage area is mainly used to stack containers without cargo. After unloading, the empty containers are stacked separately according to railway containers or cargo owners' own containers. Before loading, empty containers that meet the loading conditions are transferred from the empty container storage area. The results of the yard planning should be based on the selected entrustment, forecast and container barcode. The container area box location management system should automatically calculate the entry box times where the incoming boxes should be stacked, and group them in a list according to box type, size and other attributes. If the calculation result does not meet the conditions, it will prompt which times need to be stacked. The condition for becoming an entry box time is to match the box barcode and the box position is not full. If there are multiple conditions that meet the conditions, select the time with fewer boxes; if there is no box position, select other empty times, and give priority to the empty times that have the same attributes as the incoming boxes when they were emptied last time, and try to be the closest to the current entry box time. The main principles for assigning slots for incoming containers include: 1) First, based on the customer's slot requirements, the planner can manually specify or the system can automatically generate slots for incoming containers; 2) If there is no specification, the incoming container can only enter the incoming container times; 3) If the incoming container times are full, an alarm can be triggered and the conditions can be reset to find a location.

[0074] The container unpacking area is where containers that need to be unpacked from the yard are transported to the unpacking area for unpacking according to different container transportation requirements. The goods are then stacked at a designated location, waiting for the owner to pick them up. There are generally two types of containers that are unpacked: one is for LCL transportation, and the other is for FCL transportation.

[0075] In the damaged container area, after the containers are inspected, the damaged containers of different sizes are stored in the damaged container area and recorded after the mechanical operation is completed.

[0076] In the container repair area, when damaged containers are found in the incoming containers, the container management personnel and the container repair personnel arrange the incoming containers to enter the container repair area. The dispatcher manually specifies the location, records the container position after the stacking operation is completed, and repairs the containers in this area.

[0077] In the heavy container storage area, when heavy containers come in, their stacking locations will be recorded after the operation is completed. Containers of different sizes should be stored separately and can be stacked separately according to whether the same container type and the same train number are specified. When allocating locations for heavy containers coming in, try to stack them together according to the containers on the same pick list. Based on business needs and the requirements for fast and efficient on-site operations, the container location management in the container area of ​​Xi'an International Port should be designed to stack containers of different attributes separately.

[0078] Temporary storage area: temporarily stored containers enter this area and no unpacking operation is performed. The location is recorded after the machine is completed and different sizes are stored separately.

[0079] When the journey time of the lower container in the same container space is earlier than the departure time of the upper container, a container jam occurs. For each layer of containers in the same container space, the total number of containers that constitute a container jam on the upper layer is called the number of containers jammed.

[0080] In the mixed stacking mode, the railway container yard storage space resource scheduling process includes two steps: DX type and DF type, container allocation to the yard box area and assignment of specific box positions in the box area. It is mainly to reasonably determine the number of box areas for sending containers and assign box positions based on the yard classification standards and stacking rules, balance the workload of each box area, and minimize the number of box unloading within an operation task or an operation cycle. Balance the workload of each box area in the yard to balance the overall box volume in the yard box area and improve the utilization efficiency of storage space resources and equipment resources. Minimize the number of pressed boxes caused by container storage, reduce the unloading operations caused by pressed boxes, and shorten the waiting time of container trains and container trucks.

[0081] In the container area quantity optimization stage, balance the container quantity in each container area of ​​the yard, allocate DX and DF containers to each container area, balance the container quantity in each container area, ensure the balanced use of rail gantry and container space in each container area, and enable trains and container trucks to quickly load and unload containers. In the container space assignment stage, after the container area is divided into specific container areas in the container area quantity optimization stage, the DX and DF containers allocated to each container area in the container area quantity optimization stage are allocated to specific container spaces in each container area, so that the number of pressed containers generated by the storage of DX and DF containers in the yard during the planning cycle or within a certain statistical period is minimized, thereby reducing the number of container unloading times during container pickup or loading operations and improving yard operation efficiency. Optimization ideas such as Fig.10 shown.

[0082] Furthermore, the objective function of the railway container yard container quantity balanced allocation model is as follows:

[0083] Among them, w1 represents the weight coefficient of the container quantity balance of the container truck operation in the yard container area, w2 represents the weight coefficient of the container quantity balance of the train operation in the yard container area, and w3 represents the weight coefficient of the overall container quantity balance in the yard container area; express t Transported to container yard during the period and distributed to container area i The number of DF boxes loaded on the train, express t Unloading from train to container area during the period i The number of DX boxes taken away, express t The number of DT boxes picked up during the period, express t The number of DY-type containers loaded onto trains during the period, Indicates that the stack is in the box area i Zhongzai t The number of DY-type boxes loaded onto trains during this period, Indicates the number of DT boxes taken away. Indicates that the stack is in the box areai Zhongzai t The number of DT boxes taken away during the period; The constraints of the railway container yard container quantity balanced allocation model are as follows: t =1,2… T ; K =0,1… T - t t =1,2… T ; i =0,1… B , t =1,2… T ; K =0,1… T - t , t =1,2… T ; i =0,1… B , t =1,2… T ; i =0,1… B , t =1,2… T ; i =0,1… B

[0084] in, express t Transported to container yard during the period and distributed to container area i The quantity of DF type boxes, express t Transported to container yard during the period and distributed to container area i in t + k The number of DF boxes loaded on the train during the period, B Indicates the number of container areas in the yard. T Indicates the time periods contained in a planning cycle. express t Unloading from train to container area during the period i The quantity of DX boxes, express tUnloading from train to container area during the period i in t + k The number of DX boxes taken away during the period, Indicates that the stack is in the box area i Zhongzai t The number of DT boxes taken away during the period, Indicates that it has been allocated in the box area at the beginning of the planning period i in and t The number of DT boxes taken away during the period, Indicates t Unloading from train to container area during the period i in t - k The number of DX boxes taken away during the period, Indicates that the stack is in the box area i Zhongzai t The number of DY-type boxes loaded onto trains during this period, Indicates that it has been allocated in the box area at the beginning of the planning period i in and t The number of DF boxes loaded onto trains during this period, express t Transported to container yard during the period and distributed to container area i in t - k The number of DF boxes loaded on the train during the period, express t Box area at the beginning of the period i The total number of boxes in Indicates box area i storage capacity.

[0085] The overall solution process of the storage space resource scheduling optimization model is as follows: Fig.11 According to the objectives and constraints of the container yard intelligent assignment optimization model, a heuristic algorithm is designed to solve the model. The algorithm flow is as follows: S31, initializing planning cycle parameters, setting time variable t=1, and inputting container information; S32, calculating the operation volume of DF containers in each container area in the yard during period t, dividing them into each container area according to the constraint conditions, and calculating the total operation volume of the four types of containers in the yard at present, and obtaining the operation volume ranking of each container area; S33, limiting the workload of each box area and distributing it to each box area in order from low to high, and judging whether it is finished; S34, calculating the total amount of the four types of containers in each period, and calculating and storing the objective function value; S35, judging whether there is a DX container in the container area with the largest workload, if yes, proceed to S36, otherwise proceed to S37; S36, determine whether the DX-type containers leaving the market during this period are allocated to this container area because the workload of this container area is the smallest during the allocation period. If yes, proceed to S38, otherwise return to S35; S37, determine whether there is DX-type container volume in the container area with the largest operation volume during the period, if not, proceed to S39, otherwise return to S35; S8, let t = t-1, determine whether the current period is the start period of the planning cycle, calculate the objective function value, and go to S39; S39. Compare the objective function values ​​of the two calculations and take the minimum value as the objective function of the model.

[0086] This embodiment designs a traversal search algorithm based on container attributes for the separate storage mode, which improves the service capacity of the railway container yard and the quality of the slot assignment decision. For the mixed storage mode, a heuristic algorithm that adapts to large-scale and complex scenarios is designed to solve the model, which improves the service capacity of the railway container yard and the quality of the slot assignment decision.

[0087] Embodiment 2 See also Figure 2 , a railway terminal container dispatching optimization system, comprising: Constructing a railway container yard slot assignment optimization model module, which is used to construct a railway container yard slot assignment optimization model based on the yard information representation method of the slot freedom degree and the container stacking optimization process, wherein the constraint conditions of the railway container yard slot assignment optimization model are configured according to the container yard storage rules and the container stacking form, and the container yard storage rules and the container stacking form are preset according to the container attributes; The module for obtaining the optimal stacking position of the boxes to be stacked and the optimal target box position for the boxes to be picked up is used to obtain the stacking algorithm from the container yard to the train and the box picking algorithm from the train to the container yard in combination with the railway container yard box position assignment optimization model; the optimal stacking position of the boxes to be stacked is obtained by stacking the boxes from the container yard to the train, and the optimal target box position of the boxes to be picked up is extracted by using the box picking algorithm from the train to the container yard; The module for obtaining the optimal slot assignment method is used to construct a balanced allocation model for railway container yard container quantities according to the yard classification and container types that optimize storage space resources. The heuristic algorithm is used to solve the balanced allocation model for railway container yard container quantities to obtain the optimal division of container quantities in the container area. Combined with the optimal division of container quantities in the container area, the heuristic algorithm is used to solve the railway container yard slot assignment optimization model to obtain the optimal slot assignment method.

[0088] This embodiment can ensure that each yard is fully utilized and reduce the waste of idle space by accurately calculating the container volume allocation of each yard; the container slot assignment model further optimizes the use of specific container slots, ensures that the goods are stacked compactly and orderly, and maximizes space utilization; balanced container volume allocation helps to reduce the transfer of goods between yards, thereby reducing transportation costs and time; reasonable container slot assignment can reduce the moving distance of cranes or other handling equipment and improve operating efficiency; automated and intelligent scheduling optimization models help simplify management processes and reduce human errors; real-time monitoring and data analysis functions can help managers better understand the status of the yard and make more informed decisions; by optimizing space utilization and operating efficiency, energy consumption and labor costs can be reduced; the risk of cargo damage and loss is reduced, further reducing operating costs.

[0089] Embodiment 3 See also Figure 3 An electronic device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the railway terminal container scheduling optimization method when executing the computer program.

[0090] Embodiment 4 A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for optimizing railway terminal container scheduling is implemented.

[0091] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0092] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0093] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0094] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention is described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation of the present invention can still be modified or replaced by equivalents, and any modification or equivalent replacement that does not deviate from the spirit and scope of the present invention should be included in the protection scope of the claims of the present invention.

Claims

1. A railway terminal container dispatch optimization method, characterized in that: The following steps are involved: A railway container yard slot assignment optimization model is constructed based on a yard information representation method of the slot freedom and a container stacking optimization process, wherein the constraint conditions of the railway container yard slot assignment optimization model are configured according to the container yard storage rules and the container stacking form, and the container yard storage rules and the container stacking form are preset according to the container attributes; Combined with the optimization model of container yard slot assignment, the algorithm for stacking containers from the container yard to the train and the algorithm for picking up containers from the train to the container yard are obtained; the algorithm for stacking containers from the container yard to the train is used to stack the containers to be stacked to obtain the optimal stacking position, and the algorithm for picking up containers from the train to the container yard is used to extract the optimal target position for the containers to be picked up; According to the container types of yard classification and storage space resource optimization, a balanced allocation model of railway container yard container quantity is constructed. The heuristic algorithm is used to solve the balanced allocation model of railway container yard container quantity to obtain the optimal division of container quantity in container area. Combined with the optimal division of container quantity in container area, the heuristic algorithm is used to solve the railway container yard slot assignment optimization model to obtain the optimal slot assignment method.

2. A railway terminal container dispatch optimization method according to claim 1, characterized in that: The container yard storage rules include: Before the yard floor is filled, all containers are free containers and are stacked on top first. When the bottom layer of the yard is full, the remaining containers will be stacked in the order of increasing number of stacks in the yard. The target location of loading and unloading boxes and the equipment moving path are within the equipment operation area; 20-foot containers and 40-foot containers are stacked on different levels, and no containers are stacked on top of non-compressible containers; Obtain the target location of the container to be stacked or picked up within the spatial range of the yard; The container stacking forms include vertical, flat and stepped types, and the containers are stacked and retrieved by multiple operations one by one.

3. A railway terminal container dispatch optimization method according to claim 2, characterized in that: The container stacking optimization process includes: In the first stage, when the bottom layer of the yard is not full and there is some remaining space in the yard, containers of the same attributes are stacked together according to the principle of top priority; In the second stage, when the attributes of the newly entered container are different from those of the containers on the yard, the newly entered container is placed in the space where the container with the same attributes can be placed; When there is no new container with the same attributes in the yard, or the attributes of the new container are different from those of all the containers in the yard, a container pressing operation is generated; the position or position set where the new container can be placed is obtained by maximizing the total freedom of the positions of the containers in the yard; In the third stage, when the yard can no longer meet the needs of single-load containers, double-load containers are generated, and the maximum limit on the freedom of container positions on the yard is used to obtain the position where containers can be stacked or retrieved; If the stacking status on the yard during the container picking operation returns to the previous stage, the next stacking or picking operation will be carried out according to the previous stage; The degrees of freedom of the container position are: in, x ∈X, y ∈Y,( x , y )∈S, S∈X×Y, X represents the set range of positive integer horizontal coordinates of the box in the bottom projection coordinates, Y represents the set range of positive integer vertical coordinates of the box in the bottom projection coordinates, ( x , y ) is the bottom projection coordinate of the box, z is the container stacking height; S1 means that there is a container placed in the container space and it is not pressed by other containers, but the stack is not stacked to the highest level. f =1; S2 means that there is a box placed in the container position, but it is pressed by other boxes and is not in a stack of boxes with the same attributes, and the stack is not stacked to the highest position. The degree of freedom of the container position is k times the degree of freedom of the container position pressing it. S3 means that there is no box placed in the box position, and there are boxes stacked below it or there is a temporary detention mark at this position. The freedom degree of the box position is f =0; S4 means that there is a box placed in the box position, and it is in a stack with the same attributes, and the stack has been stacked to the highest level. f =2; S5 means that there are no containers stacked above or below the container space. f =3; When the adjacent containers stacked on the container are of the same attributes, k = α , α ∈[0,1] or k = β , β ∈[0,1], β < α ; The objective function of the railway container yard slot assignment optimization model is: Among them, maxZ is the objective function of the optimization model for the assignment of container slots in the railway container yard, indicating that the sum of the degrees of freedom of all the container slots in the container yard is the highest; e Represents a 0-1 variable, 1 means loading a container from a train to a container yard, 0 means picking up a container from a container yard to a train, f represents the degrees of freedom of the container position, p (y) is a decision variable, indicating the output code box position or box position; q ( d ) is the box area d The box location set; D is the set of all box cells, d ∈D; h ( y ) is a 0-1 variable, indicating whether the container is a container of a certain attribute. If yes, the value is 1, otherwise, the value is 0; g ( R ( d ), y ) is the box area d Middle box position y about R ( d ), R ( d ) is the box area d The stacking order and box location y The stacking order is based on the vertical stacking rule, starting from the smallest element, and taking the values ​​in turn. g ( R ( d ), y )=1,2,3,…, n ; L (y) is a temporary detention sign constraint; The constraints of the railway container yard slot assignment optimization model are as follows: m 2＞ m 1＞0 in, L (y) indicates that empty spaces without temporary detention marks shall be given priority when stacking containers. m 1 means there is a temporary detention sign when loading the box. m 2 means there is no temporary detention mark when stacking the box; h ( b ) indicates box b The generalized properties of h (p( y) ) represents the generalized classification attribute of the bin; The broad classification attribute is a set of classification attributes of two aspects: large box area and small box area; the large box area includes sending box area, arriving box area, international box area, refrigerated box area, special box area, empty box area, spare box area, maintenance box area, cleaning and disinfection box area; each large box area is divided into several small box areas according to the classification attributes and previous cargo flows; vertical stacking is adopted when stacking in the small box areas.

4. A railway terminal container dispatch optimization method according to claim 3, characterized in that: The algorithm for loading containers from the container yard to the train includes the following steps: S11, input the box attributes of the waiting box, and determine the box cell to which the waiting box belongs; S12, in the found box area, search from the minimum element to the maximum element according to the code-taking box sequence table of the box area, and remove the temporary detention mark for the empty box position with the temporary detention mark encountered during the search, until the first full box position is found, and mark the full box minimum element on the full box position; S13, according to the order table of the boxes in the box area, search from the minimum element to the maximum element step by step, find the first box position that can be used for box loading in the yard, and the box position has no temporary detention mark, and record the sum of the total freedom degrees of each box position in the new stacking state on the yard after the box to be stacked is stacked in the box position as the sum of the first degree of freedom. If all the box positions that can be used for box loading have temporary detention marks, go to S15; S14, according to the box picking sequence table of the box area code, search for empty box positions that can be used for stacking boxes without temporary detention marks one by one, and calculate the sum of the degrees of freedom of each box position on the stacking yard after placing the box to be stacked in the box position, and record it as the sum of the second degrees of freedom. If the sum of the second degrees of freedom is greater than the sum of the first degrees of freedom, the priority position of the stackable box is replaced with the current box position, otherwise it is retained as the original position as the priority stacking position, and go to S16; S15. If no available box position without a temporary detention mark is found in S12, all the box positions with temporary detention marks are found according to the box position sequence table, and the temporary detention marks on the box positions are removed, and then go to S13; S16, updating the freedom of the box positions in the operating box area in the yard; S17, output the coordinates of the box location that can be stacked, if not found, output no information; The algorithm for picking up boxes from a train to a box yard comprises the following steps: S21. Input the attributes of the box to be picked up and find the box cell to which the box to be picked up belongs, otherwise there is no solution information; S22, in the found container cell, search from the minimum element to the maximum element according to the container cell pick-up sequence table, find the first container with the same attributes as the container to be picked up and completely free without a temporary detention mark, and set a temporary detention mark on the container position for picking up the container. If no container that meets the conditions is found, go to S24; S23, updating the freedom of the box positions in the operating box area in the yard; S24: Output the coordinates of the box location found. If not found, output no information.

5. The method for optimizing railway terminal container dispatching according to claim 1, characterized in that: The container yard is classified into container areas, including the dispatch container area, arrival container area, international container area, customs supervision area, refrigerated container area, special container area, empty container area, spare container area, maintenance container area, and cleaning and disinfection container area; The container types for optimizing storage space resources include DX type of containers to be unloaded, DT type of containers to be picked up, DF type of containers to be dispatched, and DY type of containers to be transported; The DX type of container to be unloaded means that the container is still on the train, waiting to be unloaded and stored in the yard; The DT type of container to be picked up means that the container has been stacked in the yard and is waiting for the truck to enter the yard to pick up the container; The DF type of container to be dispatched indicates a container to be dispatched that has not yet been allocated to the yard and is waiting to be transported to the yard by a container truck for storage; The DY type of waiting box indicates a sending box that is already in the yard waiting to be loaded onto a train.

6. A railway terminal container dispatch optimization method according to claim 5, characterized in that: The objective function of the railway container yard container quantity balanced allocation model is as follows: Among them, w1 represents the weight coefficient of the container quantity balance of the container truck operation in the yard container area, w2 represents the weight coefficient of the container quantity balance of the train operation in the yard container area, and w3 represents the weight coefficient of the overall container quantity balance in the yard container area; express t Transported to container yard during the period and distributed to container area i The number of DF boxes loaded on the train, express t Unloading from train to container area during the period i The number of DX boxes taken away, express t The number of DT boxes picked up during the period, express t The number of DY-type containers loaded onto trains during the period, Indicates that the stack is in the box area i Zhongzai t The number of DY-type boxes loaded onto trains during this period, Indicates the number of DT boxes taken away. Indicates that the stack is in the box area i Zhongzai t The number of DT boxes taken away during the period; The constraints of the railway container yard container quantity balanced allocation model are as follows: t =1,2… T ; K =0,1… T - t t =1,2… T ; i =0,1… B , t =1,2… T ; K =0,1… T - t , t =1,2… T ; i =0,1… B , t =1,2… T ; i =0,1… B , t =1,2… T ; i =0,1… B in, express t Transported to container yard during the period and distributed to container area i The quantity of DF type boxes, express t Transported to container yard during the period and distributed to container area i in t + k The number of DF boxes loaded on the train during the period, B Indicates the number of container areas in the yard. T Indicates the time periods contained in a planning cycle. express t Unloading from train to container area during the period i The quantity of DX boxes, express t Unloading from train to container area during the period i in t + k The number of DX boxes taken away during the period, Indicates that the stack is in the box area i Zhongzai t The number of DT boxes taken away during the period, Indicates that it has been allocated in the box area at the beginning of the planning period i in and t The number of DT boxes taken away during the period, Indicates t Unloading from train to container area during the period i in t - k The number of DX boxes taken away during the period, Indicates that the stack is in the box area i Zhongzai t The number of DY-type boxes loaded onto trains during this period, Indicates that it has been allocated in the box area at the beginning of the planning period i in and t The number of DF boxes loaded onto trains during this period, express t Transported to container yard during the period and distributed to container area i in t - k The number of DF boxes loaded on the train during the period, express t Box area at the beginning of the period i The total box volume in Indicates box area i storage capacity.

7. A railway terminal container dispatch optimization method according to claim 6, characterized in that: The heuristic algorithm comprises the following steps: S31, initializing planning cycle parameters, setting time variable t=1, and inputting container information; S32, calculating the operation volume of DF containers in each container area in the yard during period t, dividing them into each container area according to the constraint conditions, and calculating the total operation volume of the four types of containers in the yard at present, and obtaining the operation volume ranking of each container area; S33, limiting the workload of each box area and distributing it to each box area in order from low to high, and judging whether it is finished; S34, calculating the total amount of the four types of containers in each period, and calculating and storing the objective function value; S35, judging whether there is a DX container in the container area with the largest workload, if yes, proceed to S36, otherwise proceed to S37; S36, determine whether the DX-type containers leaving the market during this period are allocated to this container area because the workload of this container area is the smallest during the allocation period. If yes, proceed to S38, otherwise return to S35; S37, determine whether there is DX-type container volume in the container area with the largest operation volume during the period, if not, proceed to S39, otherwise return to S35; S8, let t = t-1, determine whether the current period is the start period of the planning cycle, calculate the objective function value, and go to S39; S39. Compare the objective function values ​​of the two calculations and take the minimum value as the objective function of the model.

8. A railway terminal container dispatching optimization system, characterized in that: include: Constructing a railway container yard slot assignment optimization model module, which is used to construct a railway container yard slot assignment optimization model based on the yard information representation method of the slot freedom degree and the container stacking optimization process, wherein the constraint conditions of the railway container yard slot assignment optimization model are configured according to the container yard storage rules and the container stacking form, and the container yard storage rules and the container stacking form are preset according to the container attributes; The module for obtaining the optimal stacking position of the boxes to be stacked and the optimal target box position for the boxes to be picked up is used to obtain the stacking algorithm from the container yard to the train and the box picking algorithm from the train to the container yard in combination with the railway container yard box position assignment optimization model; the optimal stacking position of the boxes to be stacked is obtained by stacking the boxes from the container yard to the train, and the optimal target box position of the boxes to be picked up is extracted by using the box picking algorithm from the train to the container yard; The module for obtaining the optimal slot assignment method is used to construct a balanced allocation model for railway container yard container quantities according to the yard classification and container types that optimize storage space resources. The heuristic algorithm is used to solve the balanced allocation model for railway container yard container quantities to obtain the optimal division of container quantities in the container area. Combined with the optimal division of container quantities in the container area, the heuristic algorithm is used to solve the railway container yard slot assignment optimization model to obtain the optimal slot assignment method.

9. An electronic device, characterized in that: The invention comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, a method for optimizing railway terminal container scheduling as described in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for optimizing railway terminal container scheduling described in any one of claims 1 to 7 is implemented.

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