Spatial allocation method of bulk cargo terminal in port considering mixed layout of silo group and open yard

Abstract

The application discloses a space distribution method for a port dry bulk cargo yard with a mixed layout of silo groups and open yards, and belongs to the technical field of port logistics and production scheduling.S1: basic information of the mixed yard layout, yard operation task information and yard operation parameter information in a planning period are collected;S2: a space distribution model for the port dry bulk cargo yard considering the mixed layout is constructed, and a collaborative optimization relationship among task distribution, operation scheduling and yard rehandling operation is established;S3: based on the distribution model, the yard task and the rehandling operation in the planning period are uniformly optimized and solved.The application realizes reasonable distribution of cargos between the silo groups and the open yards by uniformly modeling and optimizing the stacking and reclaiming tasks and the rehandling operation; under the premise of meeting the yard operation efficiency, equipment capacity, inventory balance and temperature safety constraints, collaborative optimization of the yard space distribution and operation scheduling under the mixed layout is realized, and the operation efficiency, safety and economy of the port dry bulk cargo yard system are improved.

Description

Technical Field

[0001] This invention belongs to the field of port logistics and production scheduling technology, and relates to a method for allocating space in port dry bulk cargo yards that considers the mixed layout of silo clusters and open-air storage yards. Specifically, it relates to an optimized allocation method for port dry bulk cargo yard space that is suitable for the mixed layout of silo clusters and open-air storage yards. Background Technology

[0002] Bulk dry cargo, such as coal, ore, and grain, is a crucial category in the port's cargo handling system. Its storage, loading / unloading, and transshipment efficiency directly impacts port throughput capacity, operational safety, and operating costs. As a vital operational area in port production organization, the storage yard serves functions such as cargo storage, transshipment buffering, and operational coordination. Its operational efficiency directly affects cargo turnover speed, yard resource utilization, and the effectiveness of subsequent loading / unloading operations.

[0003] Compared to traditional open-air storage yards, silos offer advantages such as high operational efficiency, good sealing, and superior dust suppression, thus gradually becoming an important facility for storing dry bulk cargo in ports. Based on this, some modern ports have gradually adopted a hybrid layout where silo clusters and open-air storage yards coexist. In this model, when cargo is stored in silos for a long time and the temperature approaches a safe threshold, it is usually necessary to transfer the cargo from the silos to an open-air storage yard for cooling to prevent self-heating or even spontaneous combustion.

[0004] The hybrid layout storage unit comprises two parts: an upper open-air storage yard and a lower silo complex. The open-air storage yard features multiple parallel stockpiles, each with a work line and a stacker-reclaimer. The silo complex consists of multiple silos arranged in rows, each silo being an independent, enclosed storage unit with a conveyor belt at both the top and bottom. Silos within the same row share conveyor belts; the top conveyor belt is used for receiving and stockpiling, while the bottom conveyor belt is used for retrieving materials and, when necessary, transferring materials between silos. Stockpiling operations are conducted at the top via conveyor belts and unloading trolleys, while retrieving and transferring materials between silos at the bottom are conducted via conveyor belts and activated coal feeders.

[0005] Existing technologies also include research on optimizing space allocation and dust control in port dry bulk cargo yards. For example, Chinese invention patent CN121615987A proposes an intelligent scheduling method for dry bulk cargo yards, introducing the DQN algorithm and genetic algorithm to optimize the spatial resource allocation of dry bulk cargo yards, thereby reducing time loss costs and improving yard scheduling efficiency. However, this method mainly focuses on the optimization of spatial resource allocation and task scheduling in a single open-air yard scenario, without considering the collaborative configuration relationship between different storage facilities under the mixed layout of silo groups and open-air yards, making it difficult to meet the actual operational needs of ports with mixed layouts. Chinese invention patent CN118681343A proposes an intelligent sprinkler system for port dry bulk cargo open-air yards, which automatically adjusts the water volume and sprinkling time by calculating and analyzing on-site data to achieve intelligent sprinkler dust suppression in open-air yards and transshipment links. However, this method is still a terminal dust suppression control measure in the open-air yard operation process, mainly suppressing dust by spraying when it already exists or is about to occur, and still has certain limitations compared to the source dust suppression method of silos.

[0006] In summary, while existing technologies have made some progress in the allocation of space in port dry bulk cargo yards, most are limited to single storage facility scenarios and lack comprehensive consideration of factors such as cargo storage, self-heating risks, silo handling operations, and dust suppression costs in mixed layouts of silos and open yards. This makes it difficult to simultaneously meet the comprehensive optimization requirements of safety, efficiency, and environmental protection. Therefore, it is necessary to propose a method for allocating space in port dry bulk cargo yards that considers a mixed layout of silos and open yards, in order to achieve rational allocation of yard resources and optimized operational organization. Summary of the Invention

[0007] This invention addresses the problems of lack of unified optimization in the allocation of dry bulk cargo yard space, the risk of temperature rise in silo storage, and the interference of silo transfer operations with normal operations under the mixed layout of silo clusters and open-air storage yards in ports. It proposes a space allocation method for port dry bulk cargo yards that considers the mixed layout of silo clusters and open-air storage yards. This invention focuses on yard space allocation, stacking and retrieving operation timing, and coordination of silo transfer to open-air storage yards. By uniformly modeling and optimizing stacking and retrieving tasks and transfer operations, it achieves a reasonable allocation of cargo between silo clusters and open-air storage yards, thereby reducing task dwell time at the port, lowering dust suppression costs associated with open-air storage, and avoiding safety risks caused by silo temperature rise. Under the premise of meeting the constraints of yard operation efficiency, equipment capacity, inventory balance, and temperature safety, this invention achieves coordinated optimization of yard space allocation and operation scheduling under a mixed layout, effectively improving the operational efficiency, safety, and economy of the port dry bulk cargo yard system.

[0008] To achieve the above objectives, the present invention provides the following solution: This paper considers a space allocation method for port dry bulk cargo yards with a mixed layout of silos and open storage yards. This method allocates yard space under mixed layout conditions by constructing a collaborative optimization model for task allocation and silo handling operations, thereby achieving comprehensive optimization of yard operation efficiency and operating costs. The method includes the following steps: S1: Collect basic information on the layout of the port's mixed storage yard, information on storage yard operation tasks during the planning period, and information on storage yard operation parameters. This provides a complete and accurate input foundation for the subsequent construction of a mixed storage yard space allocation model. Specifically: S1-1: Collect basic information on the layout of port mixed storage yards. The required basic information on the layout of port mixed storage yards includes: the number and capacity of open storage yards, the number and capacity of silos, the planning period, and the unit duration.

[0009] S1-2: Collect information on yard operation tasks during the planning period. The yard operation tasks include stockpiling tasks and reclaiming tasks. The information on yard operation tasks during the planning period includes: number of tasks, task category, cargo type attribute, earliest start time of task, and task operation duration.

[0010] S1-3: Collect yard operation parameter information. This mainly includes: the types of goods stored in each stack and silo, the initial inventory and operation rate of each stack and silo, the initial temperature of each silo, the ambient temperature, the temperature rise rate of the goods in the silo, the safe temperature threshold of the silo, and the unit dust suppression cost of the open yard.

[0011] S2: Based on the basic information of the port mixed storage yard layout, storage yard operation task information, and storage yard operation parameter information obtained in S1, a port dry bulk cargo storage yard space allocation model considering the mixed layout is constructed. This port dry bulk cargo storage yard space allocation model establishes a collaborative optimization relationship between task allocation, operation scheduling, and silo handling operations based on the allocation relationship and operation sequence relationship between tasks and silos / stacking locations, combined with conveyor capacity limitations, dynamic inventory changes, and silo cargo temperature safety constraints. This provides support for reducing task congestion at the port, lowering dust suppression costs, and avoiding the risk of silo spontaneous combustion. Specifically: S2-1: After collecting yard operation task information and yard operation parameter information, the first step is to determine the scheduling optimization objective. This is based on the port dwell time of all tasks. Total dust suppression cost for all stacks of goods in the open storage yard The objective function is established by minimizing the weighted sum, as shown in formula (1). The port dwell time is determined by the time the task is completed. and the earliest time when the task can start calculate.

[0012] (1) In the formula, To represent a set of tasks, use index; Represents the collection of all open-air storage yard locations, using index; It is the set of all discrete time steps, using index. This represents the weighting coefficient for the length of time spent in port; This represents the cost weighting coefficient for dust suppression of goods in open-air storage yards; Indicates task The completion time; Indicates task The earliest possible start date for construction; This represents the dust suppression cost incurred when a unit of goods is stored in an open-air storage yard stack within a unit of time. express Time stacking position Inventory levels; S2-2: Establish constraints for task allocation and job scheduling.

[0013] After determining the scheduling optimization objective, relevant constraints are established for the stacking and reclaiming task operation plan to ensure that each task is reasonably allocated to the silo or stack location. The relevant constraints are shown in formulas (2) to (9): (2) (3) (4) (5) (6) (7) (8) (9) In the formula, , , , , The definitions are as shown above; To represent a sufficiently large constant, Represents the set of all storage units, using and index; Indicates task The beginning moment; Indicates task In storage unit The duration of the assignment. It is a 0-1 variable, where Indicates task Allocated to storage unit If you submit your homework, the value will be 0; otherwise, the value will be 0. Indicates task Types of goods; and Representing storage units and storage unit Types of goods; It is a 0-1 variable, where express Constant Task In the storage unit If the value is above, it is processed; otherwise, it is 0. It is also a 0-1 variable, where express Time Silo Moving to the stack Perform a transfer of funds; otherwise, the value is 0. The set of all silos is A subset of.

[0014] Formula (2) is used to constrain the actual start time of each task to not be earlier than its earliest possible start time, thereby ensuring that the task is executed within the feasible time window. Formula (3) is used to establish the correspondence between the task completion time, the start time of the operation, and the operation duration. Formulas (4) and (5) together ensure that each task must be assigned to one storage unit that matches the type of goods. Formulas (6), (7), and (8) are used together to associate the task allocation variable, the task start time, and the operation processing variable based on the time index, thereby ensuring that each assigned task continuously occupies the required number of time steps on its selected storage unit to complete the operation. Formula (9) is used to limit the feasibility of the silo transfer operation, that is, the transfer from silo to open storage yard can only occur between silos that match the type of goods and open storage yard stacking positions.

[0015] S2-3: Establish relevant constraints on the capacity limit of the belt conveyor.

[0016] The allocation of space in a mixed-layout port dry bulk cargo yard needs to consider the capacity limitations of the conveyor system to ensure that stacking, reclaiming, and warehousing operations can be coordinated under shared conveyor conditions, thereby ensuring the feasibility of the conveying process and the implementability of the scheduling scheme. The relevant constraints on conveyor capacity limitations are shown in formulas (10) to (13): (10) (11) (12) (13) In the formula, , , The definition is as shown above. This represents the collection of all open-air storage yard stacks. Indicates the stack position on the same stockpile. This refers to silos in the same row; they are all... A subset of. To represent a collection of stockpiles in an open-air storage yard, using index; The set of silo rows is represented by... index. This represents the set of all material retrieving tasks. This represents the set of all material handling tasks, which are all A subset of.

[0017] Formula (10) stipulates that at any given time, a single silo can handle at most one routine operation or one silo transfer operation. Formula (11) ensures that at any given time, each open-air stockpile can handle at most one routine operation or receive at most one silo transfer operation. Formula (12) stipulates that at any given time, within the same silo row, at most one material handling operation or one silo transfer operation can be performed. Formula (13) stipulates that at any given time, within the same silo row, at most one material stacking operation can be performed.

[0018] S2-4: Establish dynamic inventory constraints for storage units.

[0019] To dynamically depict the changes in storage unit inventory caused by stacking operations, dynamic inventory constraints need to be applied to the storage units, as shown in formulas (14) to (17): (14) (15) (16) (17) In the formula, , , , , The definition is as shown above. This indicates the initial inventory level of storage unit u at the beginning of the planning period; Represents storage unit The time required to store a unit of goods; Represents storage unit The time required for the goods to be picked up by the material unit; Indicates from the silo To open storage yard The time required for goods to be transferred between warehouses. This indicates the maximum storage capacity of each storage unit. Represents the set of discrete time steps The number of time steps in the time step.

[0020] Formula (14) is used to set the initial inventory level for each silo and open-air storage location. Formulas (15) and (16) dynamically update the inventory level of each silo and open-air storage location at each time point based on the impact of stacking, retrieving, and transfer operations on the inventory, thereby reflecting the dynamic changes in inventory of each storage unit. Formula (17) is used to impose capacity limits on each storage unit to ensure that the inventory level at any time does not exceed the maximum available capacity of the corresponding storage unit, thus ensuring the feasibility of the goods allocation results.

[0021] S2-5: Establish safety constraints on the temperature of goods inside the silo.

[0022] To characterize the temperature change of goods inside the silo over storage time and ensure that the temperature of goods in the silo does not exceed the safe temperature threshold, it is also necessary to establish safety constraints on the temperature of goods inside the silo. As shown in formulas (18) to (24): (18) (19) (20) (twenty one) (twenty two) (twenty three) (twenty four) In the formula, , The definition is as shown above. It is a 0-1 variable. Indicates silo exist Always in stock; otherwise, it is 0. Indicates silo exist Temperature at any moment; Indicates ambient temperature; Indicates silo The initial temperature at the beginning of the planning period; Indicates silo The safe temperature threshold; Indicates silo Temperature increment per unit time step.

[0023] Formulas (18) and (19) are used to define binary variables. The formula (20) is used to initialize the temperature of each silo at the beginning of the planning period. Formula (21) is used to apply a temperature safety threshold limit to ensure that the temperature of the goods in the silo does not exceed the preset safety upper limit at any time. The temperature safety threshold can be determined based on the critical temperature for spontaneous combustion of the goods in the silo. Formula (22) is used to ensure that the temperature of the silo remains at the normal ambient temperature level of the port when there are no goods in the silo. Formulas (23) and (24) describe the temperature evolution process of the non-empty silo in the first time step and subsequent time steps, respectively.

[0024] S2-6: Domain constraints for variable definitions in the stockyard space allocation model.

[0025] Finally, to ensure the rationality of the solution to the yard space allocation model, value range constraints are set for the task allocation, operation arrangement, and storage unit status parameters involved in the yard space allocation model to ensure that they meet the relevant physical conditions of actual yard operations. Formulas (25)–(28) give the value restrictions for relevant parameters (including task start and end times, task allocation variables, warehouse transfer operation arrangement variables, and storage unit inventory status). Where, Represents the set of non-negative integers.

[0026] (25) (26) (27) (28) S3: Based on the port dry bulk cargo yard space allocation model considering a mixed layout constructed in S2, a unified optimization solution is performed for yard tasks and silo transfer operations during the planning period. By solving the yard space allocation model, the storage unit allocation results, specific operation sequences, and silo transfer arrangements corresponding to each task are generated. Simultaneously, the real-time inventory status of each stack and the real-time temperature and inventory status of each silo are clarified. The solution results are further transformed into executable scheduling instructions for the terminal yard system, used to guide the execution sequence of tasks and the flow of goods between silos and open yards, thereby achieving efficient connection of yard operations under a mixed storage layout and optimizing overall operational efficiency and dust suppression costs. Specifically: S3-1: The Large Neighborhood Search (LNS) algorithm is combined with the Mixed Integer Programming (MIP) solution strategy. Based on the initial yard operation allocation and scheduling scheme, the LNS algorithm iteratively optimizes the current feasible scheduling scheme through a "destruction-repair" process. The destruction operator removes yard operation tasks and related warehouse transfer arrangements that significantly impact the objective function, freeing up storage units and time resources. The repair operator re-inserts the removed tasks into the schedule to be repaired and redetermines their storage unit allocation, start time, and necessary warehouse transfer arrangements. By repeatedly executing the destruction and repair operators, a better yard space allocation scheme is searched within the neighborhood of the current scheduling scheme. The specific steps are as follows: S3-1-1: Generate initial stockpile operation allocation and scheduling scheme: Construct an initial task sequence based on the earliest start time of each stockpiling task and reclaiming task, and determine the start time of each task, storage unit allocation result and necessary silo transfer operation arrangement one by one according to the current task sequence, so as to obtain a feasible scheduling scheme including task operation time, inventory status and silo temperature status.

[0027] S3-1-2: Execution of the destructive operator: Sort each task in the current scheduling scheme according to its influence on the objective function (formula (1)) from largest to smallest, and select the top... Each task is designated as a critical task, and the critical tasks and their associated allocation results are removed from the current scheduling scheme to free up some storage units and time resources, forming a scheduling scheme to be repaired.

[0028] The task impact is determined based on the two components of the current feasible scheduling scheme in the objective function formula (1). For any farm operation task... Its task impact Represented as: (29) in, Indicates the tasks under the current feasible scheduling scheme. The corresponding port dwelling time value in formula (1) is: Indicates the tasks under the current feasible scheduling scheme. The corresponding value for dust suppression cost of open-air storage yard in formula (1). , These represent the weighting coefficients for port delay duration and dust suppression cost in the task impact calculation, respectively. Sort the tasks from largest to smallest and select the top ones. One task is designated as a key task, among which , To preset the damage ratio, This is a set of yard operation tasks.

[0029] S3-1-3: Repair Operator Execution: Based on the repair scheduling scheme formed in S3-1-2, the removed critical tasks are re-inserted as tasks to be inserted. During the insertion process, feasible storage units and feasible start times of the tasks to be inserted are enumerated to form candidate insertion positions; among them, feasible storage units are silos or open-air storage yard stacks that meet the requirements of cargo type matching and capacity constraints, and feasible start times are the times that meet the earliest start time of the task, equipment occupancy status, and model constraints. According to the principle of minimum incremental cost, the position that minimizes the increase in the objective function, i.e., formula (1), is selected from the candidate insertion positions as the actual insertion position.

[0030] S3-1-4: Iterative Update and Termination Condition: Using the currently updated feasible scheduling scheme in S3-1-3 as the basis for the next round of search, S3-1-2 and S3-1-3 are repeatedly executed to continuously iterate and optimize the task allocation results, operation sequence, and warehouse transfer arrangements until the preset maximum number of iterations is reached. The final output is a mixed-layout port dry bulk cargo yard space allocation scheme, yielding the solution result of the large neighborhood search algorithm.

[0031] S3-2: Based on the solution results of the large neighborhood search algorithm, the start and end times of the stockpiling and reclaiming tasks, as well as the storage unit allocation results, are determined, and the silo transfer operation arrangement is derived. The solution results can be used to guide the terminal operator in formulating detailed operation plans and silo transfer arrangements, achieving efficient coordination between silo groups and open storage yards, and providing a basis for decision-making to reduce task delay time and dust suppression costs.

[0032] The beneficial effects of this invention are: The innovation of this invention is mainly reflected in the model construction in step S2. Step S2 incorporates task allocation and operation scheduling, conveyor capacity limit, dynamic inventory of storage units and temperature safety constraints of goods in silos into a unified optimization model through formulas (1) to (28), thereby realizing the coordinated optimization of storage space allocation and operation scheduling under the mixed layout of silo groups and open storage yards.

[0033] (1) This invention realizes the unified coordination of stockpiling tasks, reclaiming tasks and warehouse transfer operations by constructing a port dry bulk cargo yard space allocation model that considers mixed layout.

[0034] (2) The present invention constructs a port dry bulk cargo yard space allocation model through step S2, and combines it with the solution strategy of step S3-1 to achieve coordinated optimization of yard operation task allocation, dynamic inventory changes, silo temperature safety control and silo transfer arrangement, thereby effectively shortening the time of task delay at the port, reducing the cost of dust suppression in open yards, and reducing the safety risks caused by the temperature rise of silo cargo.

[0035] In summary, this invention can optimize task scheduling and storage space allocation in a mixed layout of silo clusters and open storage yards while ensuring the operational efficiency of dry bulk cargo terminals, providing an effective solution for intelligent scheduling and green operation of ports. Attached Figure Description

[0036] Figure 1 This is a plan of a mixed-layout dry bulk cargo yard at a port.

[0037] Figure 2 This is a flowchart of the port dry bulk cargo yard space allocation method of the present invention. Detailed Implementation

[0038] The following will combine Figure 1 and Figure 2 The technical solution of the present invention will be described in detail below.

[0039] like Figure 1 As shown, this invention addresses the problems of lack of unified optimization in the space allocation of dry bulk cargo storage yards under mixed layouts of silos and open-air storage yards in ports, the risk of temperature rise during silo storage, and the disruption of normal operations caused by silo transfer operations. It proposes a space allocation method for dry bulk cargo storage yards in ports considering the mixed layout of silos and open-air storage yards. This invention performs unified modeling and coordinated optimization of space allocation, stacking and retrieving operation sequence, and silo transfer operations, achieving a reasonable allocation of cargo between silos and open-air storage yards. This reduces port dwell time, lowers dust suppression costs, avoids safety risks caused by silo temperature rise, and improves the operational efficiency, safety, and economy of the storage yard system. Figure 2 As shown, the method for allocating space in a port dry bulk cargo yard includes the following steps: S1: Collect basic information on the layout of the port's mixed storage yard, information on storage yard operation tasks during the planning period, and information on storage yard operation parameters to lay a complete and accurate input foundation for the subsequent construction of the storage yard space allocation model; specifically: S1-1: Collect basic information on the layout of the port's mixed storage yard. Figure 1This illustration showcases a port dry bulk cargo yard with a mixed layout of silos and open-air storage. The upper part is an open-air storage yard, and the lower part is a silo complex. Two parallel stockpiles are arranged in the open-air storage yard, each divided into nine stacking positions, for a total of 18 stacking positions used to store bulk cargo for different yard operations. Each stockpile is equipped with one track, one stacker-reclaimer, and one belt conveyor. The silo complex consists of four rows, each row containing 12 silos, for a total of 48 silos used to store different types of cargo. For standardized model representation, this embodiment uses a unified numbering system for the open-air storage positions and silos as storage units. Silos in the same row share belt conveyors, with one belt conveyor at the top and one at the bottom of each row. The top uses belt conveyors and unloading trolleys for stacking operations, while the bottom uses belt conveyors and activated coal feeders for reclaiming and silo transfer operations. The capacity of a single stacking position and silo is 30,000 tons. Each task selects a corresponding stacking position or silo for operation. The planning period is 1 day, with each unit lasting 1 hour, meaning the planning period is divided into 24 time units.

[0040] S1-2: Collect information on yard operation tasks during the planning period. The yard operation tasks include stockpiling tasks and reclaiming tasks. The information on yard operation tasks during the planning period includes: number of tasks, task type, earliest start time of the task, and task duration. The collected information on tasks awaiting processing is shown in Table 1. Table 1: Task Information Table

[0041] S1-3: Collect yard operation parameter information. The ambient temperature is 30℃, the temperature rise rate of the goods inside the silo is 1℃ / hour, and the safe temperature threshold of the silo is 50℃. The unit dust suppression cost of the open-air yard is 0.02 yuan / (ton·hour). The main operating equipment involved in the yard includes stacker-reclaimers, top unloading trolleys of the silos, and bottom activated coal feeders. The stacker-reclaimer has a stacking rate of 6000 tons / hour and a reclaiming rate of 3000 tons / hour. The silo unloading trolley has a stacking rate of 6000 tons / hour, and the activated coal feeder has a reclaiming rate of 6000 tons / hour.

[0042] S2: Based on the basic information of the port mixed storage yard layout, storage yard operation task information, and storage yard operation parameter information obtained in S1, a port dry bulk cargo storage yard space allocation model considering the mixed layout is constructed. This port dry bulk cargo storage yard space allocation model establishes a collaborative optimization relationship between task allocation, operation scheduling, and silo handling operations based on the allocation relationship and operation sequence relationship between tasks and silos / stacking locations, combined with conveyor capacity limitations, dynamic inventory changes, and silo cargo temperature safety constraints. This provides support for reducing task congestion at the port, lowering dust suppression costs, and avoiding the risk of silo spontaneous combustion. Specifically: S2-1: After collecting yard operation task information and yard operation parameter information, the first step is to determine the scheduling optimization objective. This is based on the port dwell time of all tasks. Total dust suppression cost for all stacks of goods in the open storage yard The objective function is established by minimizing the weighted sum, as shown in formula (1). The port dwell time is determined by the time the task is completed. and the earliest time when the task can start calculate.

[0043] (1) In the formula, To represent a set of tasks, use index; Represents the collection of all open-air storage yard locations, using index; It is the set of all discrete time steps, using index. This represents the weighting coefficient for the length of stay in port, which is set to 1. This represents the cost weighting coefficient for dust suppression of goods in open-air storage yards, set to 1. Indicates task The completion time; Indicates task The earliest possible start date for construction; This represents the dust suppression cost incurred when a unit of goods is stored in an open-air storage yard stack within a unit of time. express Time stacking position Inventory levels; S2-2: Establish constraints for task allocation and job scheduling.

[0044] After determining the scheduling optimization objective, relevant constraints are established for the stacking and reclaiming task operation plan to ensure that each task is reasonably allocated to the silo or stack location. The relevant constraints are shown in formulas (2) to (9): (2) (3) (4) (5) (6) (7) (8) (9) In the formula, , , , , The definitions are as shown above; To represent a sufficiently large constant, Represents the set of all storage units, using and index; Indicates task The beginning moment; Indicates task In storage unit The duration of the assignment. It is a 0-1 variable, where Indicates task Allocated to storage unit If you submit your homework, the value will be 0; otherwise, the value will be 0. Indicates task Types of goods; and Representing storage units and storage unit Types of goods; It is a 0-1 variable, where express Constant Task In the storage unit If the value is above, it is processed; otherwise, it is 0. It is also a 0-1 variable, where express Time Silo Moving to the stack Perform a transfer of funds; otherwise, the value is 0. The set of all silos is A subset of.

[0045] Formula (2) is used to constrain the actual start time of each task to not be earlier than its earliest possible start time, thereby ensuring that the task is executed within the feasible time window. Formula (3) is used to establish the correspondence between the task completion time, the start time of the operation, and the operation duration. Formulas (4) and (5) together ensure that each task must be assigned to one storage unit that matches the type of goods. Formulas (6), (7), and (8) are used together to associate the task allocation variable, the task start time, and the operation processing variable based on the time index, thereby ensuring that each assigned task continuously occupies the required number of time steps on its selected storage unit to complete the operation. Formula (9) is used to limit the feasibility of the silo transfer operation, that is, the transfer from silo to open storage yard can only occur between silos that match the type of goods and open storage yard stacking positions.

[0046] S2-3: Establish relevant constraints on the capacity limit of the belt conveyor.

[0047] The allocation of space in a mixed-layout port dry bulk cargo yard needs to consider the capacity limitations of the conveyor system to ensure that stacking, reclaiming, and warehousing operations can be coordinated under shared conveyor conditions, thereby ensuring the feasibility of the conveying process and the implementability of the scheduling scheme. The relevant constraints on conveyor capacity limitations are shown in formulas (10) to (13): (10) (11) (12) (13) In the formula, , , The definition is as shown above. This represents the collection of all open-air storage yard locations. Indicates the stack position on the same stockpile. This refers to silos in the same row; they are all... A subset of. To represent a collection of stockpiles in an open-air storage yard, using index; The set of silo rows is represented by... index. This represents the set of all material retrieving tasks. This represents the set of all material handling tasks, which are all A subset of.

[0048] Formula (10) stipulates that at any given time, a single silo can handle at most one routine operation or one silo transfer operation. Formula (11) ensures that at any given time, each open-air stockpile can handle at most one routine operation or receive at most one silo transfer operation. Formula (12) stipulates that at any given time, within the same silo row, at most one material handling operation or one silo transfer operation can be performed. Formula (13) stipulates that at any given time, within the same silo row, at most one material stacking operation can be performed.

[0049] S2-4: Establish dynamic inventory constraints for storage units.

[0050] To dynamically depict the changes in storage unit inventory caused by stacking operations, dynamic inventory constraints need to be applied to the storage units. As shown in equations (14) to (17): (14) (15) (16) (17) In the formula, , , , , The definition is as shown above. This indicates the initial inventory level of storage unit u at the beginning of the planning period; Represents storage unit The time required to store a unit of goods; Represents storage unit The time required for the goods to be picked up by the material unit; Indicates from the silo To open storage yard The time required for goods to be transferred between warehouses. This indicates the maximum storage capacity of each storage unit. Represents the set of discrete time steps The number of time steps in the time step.

[0051] Formula (14) is used to set the initial inventory level for each silo and open-air storage location. Formulas (15) and (16) dynamically update the inventory level of each silo and open-air storage location at each time point based on the impact of stacking, retrieving, and transfer operations on the inventory, thereby reflecting the dynamic changes in inventory of each storage unit. Formula (17) is used to impose capacity limits on each storage unit to ensure that the inventory level at any time does not exceed the maximum available capacity of the corresponding storage unit, thus ensuring the feasibility of the goods allocation results.

[0052] S2-5: Establish safety constraints on the temperature of goods inside the silo.

[0053] To characterize the temperature change of goods inside the silo over storage time and ensure that the temperature of goods in the silo does not exceed the safe temperature threshold, it is also necessary to establish safety constraints on the temperature of goods inside the silo. As shown in formulas (18) to (24): (18) (19) (20) (twenty one) (twenty two) (twenty three) (twenty four) In the formula, , The definition is as shown above. It is a 0-1 variable. Indicates silo exist Always in stock; otherwise, it is 0. Indicates silo exist Temperature at any moment; Indicates ambient temperature; Indicates silo The initial temperature at the beginning of the planning period; Indicates silo The safe temperature threshold; Indicates silo Temperature increment per unit time step.

[0054] Formulas (18) and (19) are used to define binary variables to represent the inventory status of the silos. Formula (20) is used to initialize the temperature of each silo at the beginning of the planning period. Formula (21) is used to apply a temperature safety threshold limit to ensure that the temperature of the goods in the silo does not exceed the preset safety upper limit at any time. The temperature safety threshold can be determined based on the critical temperature for spontaneous combustion of the goods in the silo. Formula (22) is used to ensure that the temperature of the silo remains at the normal ambient temperature level of the port when there are no goods in the silo. Formulas (23) and (24) describe the temperature evolution process of the non-empty silos in the first time step and subsequent time steps, respectively.

[0055] S2-6: Domain constraints for variables in the stockyard space allocation model.

[0056] Finally, to ensure the rationality of the solution to the yard space allocation model, value range constraints are set for the task allocation, operation arrangement, and storage unit status parameters involved in the yard space allocation model to ensure that they meet the relevant physical conditions of actual yard operations. Formulas (25)–(28) give the value restrictions for relevant parameters (including task start and end times, task allocation variables, warehouse transfer operation arrangement variables, and storage unit inventory status). Where, Represents the set of non-negative integers.

[0057] (25) (26) (27) (28) S3: Based on the port dry bulk cargo yard space allocation model considering a mixed layout constructed in S2, a unified optimization solution is performed for yard tasks and silo transfer operations during the planning period. By solving the yard space allocation model, the storage unit allocation results, specific operation sequences, and silo transfer arrangements corresponding to each task are generated. Simultaneously, the real-time inventory status of each stack and the real-time temperature and inventory status of each silo are clarified. The solution results are further transformed into executable scheduling instructions for the terminal yard system, used to guide the execution sequence of tasks and the flow of goods between silos and open yards, thereby achieving efficient connection of yard operations under a mixed storage layout and optimizing overall operational efficiency and dust suppression costs. Specifically: S3-1: This embodiment employs the Large Neighborhood Search (LNS) algorithm combined with the Mixed Integer Programming (MIP) solution strategy. Based on the initial yard operation allocation and scheduling scheme, the LNS algorithm iteratively optimizes the current feasible scheduling scheme through a "destruction-repair" process. The destruction operator removes yard operation tasks and related warehouse transfer arrangements that significantly impact the objective function, freeing up storage units and time resources. The repair operator re-inserts the removed tasks into the schedule to be repaired and redetermines their storage unit allocation, start time, and necessary warehouse transfer arrangements. By repeatedly executing the destruction and repair operators, a better yard space allocation scheme is searched within the neighborhood of the current scheduling scheme. The specific steps are as follows: S3-1-1: Generate initial stockpile operation allocation and scheduling scheme: Construct an initial task sequence based on the earliest start time of each stockpiling task and reclaiming task, and determine the start time of each task, storage unit allocation result and necessary silo transfer operation arrangement one by one according to the current task sequence, so as to obtain a feasible scheduling scheme including task operation time, inventory status and silo temperature status.

[0058] S3-1-2: Execution of the destructive operator: Sort each task in the current scheduling scheme according to its influence on the objective function (formula (1)) from largest to smallest, and select the top... Each task is designated as a critical task, and the critical tasks and their associated allocation results are removed from the current scheduling scheme to free up some storage units and time resources, forming a scheduling scheme to be repaired.

[0059] The task impact is determined based on the two components of the current feasible scheduling scheme in the objective function formula (1). For any farm operation task... Its task impact Represented as: (29) in, Indicates the tasks under the currently feasible scheduling scheme. The corresponding port dwelling time value in formula (1) is: Indicates the tasks under the currently feasible scheduling scheme. The corresponding value for dust suppression cost of open-air storage yard in formula (1). , These represent the weighting coefficients for port delay duration and dust suppression cost in the task impact calculation, respectively. Sort the tasks from largest to smallest and select the top ones. One task is designated as a key task, among which , To preset the damage ratio, This is a set of yard operation tasks.

[0060] S3-1-3: Repair Operator Execution: Based on the repair scheduling scheme formed in S3-1-2, the removed critical tasks are re-inserted as tasks to be inserted. During the insertion process, feasible storage units and feasible start times of the tasks to be inserted are enumerated to form candidate insertion positions; among them, feasible storage units are silos or open-air storage yard stacks that meet the requirements of cargo type matching and capacity constraints, and feasible start times are the times that meet the earliest start time of the task, equipment occupancy status, and model constraints. According to the principle of minimum incremental cost, the position that minimizes the increase in the objective function, i.e., formula (1), is selected from the candidate insertion positions as the actual insertion position.

[0061] S3-1-4: Iterative Update and Termination Condition: Using the currently updated feasible scheduling scheme in S3-1-3 as the basis for the next round of search, S3-1-2 and S3-1-3 are repeatedly executed to continuously iterate and optimize the task allocation results, operation sequence, and warehouse transfer arrangements until the preset maximum number of iterations is reached. The final output is a mixed-layout port dry bulk cargo yard space allocation scheme, yielding the solution result of the large neighborhood search algorithm.

[0062] S3-2: Based on the solution results of the large neighborhood search algorithm, the start and end times of the stockpiling and reclaiming tasks, as well as the storage unit allocation results, are determined, and the silo transfer operation arrangement is derived. The solution results can be used to guide the terminal operator in formulating detailed operation plans and silo transfer arrangements, achieving efficient coordination between silo groups and open storage yards, and providing a basis for decision-making to reduce task delay time and dust suppression costs.

[0063] The solution results are shown in Table 2: Table 2: Results of the Work Schedule Solution

[0064] Table 3: Results of Solving the Warehouse Transfer Operation Arrangement

[0065] Analysis of Table 2 shows that all 10 yard operations were scheduled and allocated storage units within the planning period. Except for Tasks 2 and 9, which were delayed due to constraints such as storage unit occupancy, conveyor capacity, and silo relocation coordination, the remaining tasks were executed at their earliest start times. Except for Task 10, which was assigned to stack location 24, all other tasks were assigned to silos, indicating that the model prioritizes the use of silos for enclosed storage, thereby reducing open yard occupancy and dust suppression costs. Analysis of Table 3 shows that the model arranged three silo relocation operations, with silos 2, 45, and 27 being moved to their corresponding stack locations. This silo relocation arrangement, while meeting constraints on cargo type matching, capacity limitations, and operation timing, frees up silo space and reduces the risk of cargo temperature rise in silos, achieving coordinated scheduling between the silo group and the open yard.

[0066] This invention discloses a method for allocating space in port dry bulk cargo yards considering a mixed layout of silos and open storage yards. By constructing a collaborative optimization model for task allocation, task sequencing, and silo transfer decisions, it achieves overall optimization of the mixed-layout yard space and operational processes. Based on the port's mixed yard layout, task characteristics, and related parameter information, this invention performs correlation modeling on open storage yard stack allocation, silo storage, and silo transfer processes, thereby dynamically adjusting the task sequence, space allocation, and silo transfer scheme. This invention can reduce task delays and open-air yard dust suppression costs while ensuring yard operational efficiency, and avoid safety risks caused by temperature rise in silo cargo, providing an effective solution for intelligent port scheduling, safe production, and green operation.

[0067] It should be noted that the above embodiments are merely illustrative of the implementation methods of the present invention, but should not be construed as limiting the scope of the present invention. It should be pointed out that those skilled in the art can make several modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention.

Claims

1. A method for allocating space in port dry bulk cargo storage yards considering a mixed layout of silo clusters and open storage yards, characterized in that, The port dry bulk cargo yard space allocation method, by constructing a collaborative optimization model for task allocation and warehouse transfer operations, allocates yard space under mixed layout yard conditions, achieving comprehensive optimization of yard operation efficiency and operating costs; it includes the following steps: S1: Collect basic information on the layout of the port's mixed storage yard, information on storage yard operation tasks during the planning period, and information on storage yard operation parameters to lay a complete and accurate input foundation for the subsequent construction of a mixed storage yard space allocation model; S2: Based on the basic information of the port mixed storage yard layout, storage yard operation task information, and storage yard operation parameter information obtained in S1, a port dry bulk cargo storage yard space allocation model considering the mixed layout is constructed. This model establishes a collaborative optimization relationship between task allocation, operation scheduling, and silo handling operations based on the allocation relationship between tasks and silos / stacking locations, as well as the operation sequence relationship, combined with conveyor capacity limitations, dynamic inventory changes, and silo cargo temperature safety constraints. Specifically: S2-1: After collecting information on yard operation tasks and yard operation parameters, first determine the scheduling optimization objective; S2-2: Establish constraints for task allocation and job scheduling; S2-3: Establish relevant constraints for the capacity limit of the belt conveyor; S2-4: Establish dynamic inventory constraints for storage units; S2-5: Establish safety constraints for cargo temperature inside silos; S2-6: Domain constraints for variables in the stockyard space allocation model; S3: Based on the port dry bulk cargo yard space allocation model considering mixed layout constructed in S2, the yard tasks and silo transfer operations during the planning period are uniformly optimized and solved. By solving the yard space allocation model, the storage unit allocation results, specific operation sequence and silo transfer arrangements corresponding to each task are generated. At the same time, the real-time inventory status of each stack and the real-time temperature and inventory status of each silo are clarified. The solution results are further transformed into executable scheduling instructions for the terminal yard system to guide the execution order of tasks and the flow of goods between silos and open yards.

2. The port dry bulk cargo storage yard space allocation method considering the mixed layout of silo groups and open storage yards according to claim 1, characterized in that, Specifically, S1 refers to: The basic information on the layout of the port's mixed storage yard includes: the number and capacity of open storage yards, the number and capacity of silos, the planning period, and the unit duration; The yard operation tasks include stockpiling tasks and reclaiming tasks. The yard operation task information during the planning period includes: task quantity, task category, cargo type attribute, earliest start time of task, and task operation duration. The yard operation parameters include: the types of goods stored in each stack and silo, the initial inventory and operation rate of each stack and silo, the initial temperature of each silo, the ambient temperature, the temperature rise rate of the goods in the silo, the safe temperature threshold of the silo, and the unit dust suppression cost of the open-air yard.

3. The port dry bulk cargo storage yard space allocation method considering the mixed layout of silo groups and open storage yards according to claim 2, characterized in that, Specifically, S2-1 includes: Based on the length of stay in Hong Kong for all tasks Total dust suppression cost for all stacks of goods in the open storage yard The objective function is established by minimizing the weighted sum, as shown in formula (1); where the task's port dwell time is determined by the task completion time. and the earliest time when the task can start calculate; (1) In the formula, To represent a set of tasks, use index; Represents the collection of all open-air storage yard locations, using index; It is the set of all discrete time steps, using index; This represents the weighting coefficient for the length of time spent in port; This represents the cost weighting coefficient for dust suppression of goods in open-air storage yards; Indicates task The completion time; Indicates task The earliest possible start date for construction; This represents the dust suppression cost incurred when a unit of goods is stored in an open-air storage yard stack within a unit of time. express Time stacking position Inventory levels.

4. The port dry bulk cargo storage yard space allocation method considering the mixed layout of silo groups and open storage yards according to claim 3, characterized in that, Specifically, S2-2 includes: After determining the scheduling optimization objective, relevant constraints are established for the work plan of stacking and reclaiming tasks to ensure that each task is reasonably allocated to silos or stack locations; the relevant constraints are shown in formulas (2) to (9): (2) (3) (4) (5) (6) (7) (8) (9) In the formula, , , , , The definitions are as shown above; To represent a sufficiently large constant, Represents the set of all storage units, using and index; Indicates task The beginning moment; Indicates task In storage unit The duration of the assignment; It is a 0-1 variable, where Indicates task Allocated to storage unit If you submit your homework, the value will be 0; otherwise, the value will be 0. Indicates task Types of goods; and Representing storage units and storage unit Types of goods; It is a 0-1 variable, where express Constant Task In the storage unit If the value is above, it is processed; otherwise, it is 0. It is also a 0-1 variable, where express Time Silo Moving to the stack Perform a transfer of funds; otherwise, the value is 0. The set of all silos is A subset of.

5. The port dry bulk cargo storage yard space allocation method considering the mixed layout of silo groups and open storage yards according to claim 4, characterized in that, Specifically, S2-3 includes: The allocation of space in a mixed-layout port dry bulk cargo yard needs to take into account the capacity limitations of the belt conveyor system. The relevant constraints on the capacity limitations of the belt conveyor are shown in formulas (10) to (13): (10) (11) (12) (13) In the formula, , , The definitions are as shown above; This represents the collection of all open-air storage yard locations. Indicates the stack position on the same stockpile. This refers to silos in the same row; they are all... A subset of; To represent a collection of stockpiles in an open-air storage yard, using index; The set of silo rows is represented by... index; This represents the set of all material retrieving tasks. This represents the set of all material handling tasks, which are all A subset of.

6. The port dry bulk cargo storage yard space allocation method considering the mixed layout of silo groups and open storage yards according to claim 5, characterized in that, Specifically, S2-4 includes: To dynamically depict the changes in storage unit inventory caused by stacking operations, dynamic inventory constraints are applied to the storage units, as shown in formulas (14) to (17): (14) (15) (16) (17) In the formula, , , , , The definitions are as shown above; This indicates the initial inventory level of storage unit u at the beginning of the planning period; Represents storage unit The time required to store a unit of goods; Represents storage unit The time required for the goods to be picked up by the material unit; Indicates from the silo To open storage yard The time required for goods to be transferred between warehouses; This indicates the maximum storage capacity of each storage unit; Represents the set of discrete time steps The number of time steps in the time step.

7. The port dry bulk cargo storage yard space allocation method considering the mixed layout of silo groups and open storage yards according to claim 6, characterized in that, Specifically, S2-5 includes: To characterize the temperature change of goods inside the silo over storage time and ensure that the temperature of goods in the silo does not exceed the temperature safety threshold, a temperature safety constraint for goods inside the silo is established, as shown in formulas (18) to (24): (18) (19) (20) (21) (22) (23) (24) In the formula, , The definitions are as shown above; It is a 0-1 variable. Indicates silo exist Always in stock; otherwise, it is 0. Indicates silo exist Temperature at any moment; Indicates ambient temperature; Indicates silo The initial temperature at the beginning of the planning period; Indicates silo The safe temperature threshold; Indicates silo Temperature increment per unit time step.

8. The port dry bulk cargo storage yard space allocation method considering the mixed layout of silo groups and open storage yards according to claim 7, characterized in that, Specifically, S2-6 includes: To ensure the rationality of the solution to the yard space allocation model, value range constraints are set for the task allocation, operation arrangement, and storage unit status parameters involved in the yard space allocation model to ensure that they meet the relevant physical conditions of actual yard operations; Formulas (25)–(28) give the value restrictions for task start and end times, task allocation variables, warehouse transfer operation arrangement variables, and storage unit inventory status; where, Represents the set of non-negative integers; (25) (26) (27) (28)。 9. The port dry bulk cargo storage yard space allocation method considering the mixed layout of silo groups and open storage yards according to claim 8, characterized in that, Specifically, S3 is as follows: S3-1: The solution strategy combines the Large Neighborhood Search (LNS) algorithm with Mixed Integer Programming (MIP). Based on the initial yard operation allocation and scheduling scheme, the large neighborhood search algorithm iteratively optimizes the current feasible scheduling scheme through a destruction operator and a repair operator. The destruction operator is used to remove yard operation tasks and related warehouse transfer arrangements that have a significant impact on the objective function, thereby freeing up storage units and time resources. The repair operator is used to reinsert the removed tasks into the scheduling scheme to be repaired, and redetermine their storage unit allocation, start time, and necessary warehouse transfer arrangements. By repeatedly executing the destruction operator and the repair operator, a better yard space allocation scheme is searched within the neighborhood of the current scheduling scheme. S3-2: Based on the solution results of the large neighborhood search algorithm, determine the start time and completion time of the stacking and retrieving tasks, as well as the storage unit allocation results, and obtain the warehouse transfer operation arrangement.

10. The port dry bulk cargo storage yard space allocation method considering the mixed layout of silo groups and open storage yards according to claim 9, characterized in that, Specifically, S3-1 includes: S3-1-1: Generate initial stockpile operation allocation and scheduling scheme: Construct an initial task sequence based on the earliest start time of each stockpile task and reclaiming task, and determine the start time of each task, storage unit allocation result and necessary silo transfer operation arrangement one by one according to the current task sequence, so as to obtain a feasible scheduling scheme including task operation time, inventory status and silo temperature status. S3-1-2: Execution of the disruption operator: Sort each task in the current scheduling scheme according to its influence on the objective function (formula (1)) from largest to smallest, and select the top... Each task is designated as a critical task, and the critical task and its related allocation results are removed from the current scheduling scheme to free up some storage units and time resources, forming a scheduling scheme to be repaired. The impact of the task is determined based on the two components of the current feasible scheduling scheme in the objective function formula (1); for any farm operation task Its task impact Represented as: (29) in, Indicates the tasks under the current feasible scheduling scheme. The corresponding port dwelling time value in formula (1) is: Indicates the tasks under the currently feasible scheduling scheme. The corresponding value for dust suppression cost of open-air storage yard in formula (1); , These represent the weighting coefficients for port delay duration and dust suppression cost in the task impact calculation, respectively; according to Sort the tasks from largest to smallest and select the top ones. One task is designated as a key task, among which , To preset the damage ratio, A set of yard operation tasks; S3-1-3: Repair Operator Execution: Based on the repair scheduling scheme formed in S3-1-2, the removed critical tasks are re-inserted as tasks to be inserted; during the insertion process, the feasible storage units and feasible start times of the tasks to be inserted are enumerated to form candidate insertion positions; among them, the feasible storage units are silos or open-air storage yard stacks that meet the matching of cargo types and capacity limits, and the feasible start times are the times that meet the earliest start times of the task, equipment occupancy status and model constraints; according to the principle of minimum incremental cost, the position that minimizes the increase of the objective function, i.e., formula (1), is selected from the candidate insertion positions as the actual insertion position; S3-1-4: Iterative Update and Termination Condition: Using the currently updated feasible scheduling scheme in S3-1-3 as the basis for the next round of search, S3-1-2 and S3-1-3 are repeatedly executed to continuously iterate and optimize the task allocation results, operation sequence and warehouse transfer arrangements until the preset maximum number of iterations is reached; finally, the mixed layout port dry bulk cargo yard space allocation scheme is output, and the solution result of the large neighborhood search algorithm is obtained.

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