Inland river container wharf yard crane scheduling method considering instruction priority

Abstract

The invention belongs to the technical field of logistics scheduling, and particularly relates to an inland river container wharf field bridge scheduling method considering instruction priority, which enables a field bridge scheduling scheme to better conform to an actual scene of inland river port field bridge scheduling by introducing instruction execution priority, and further uses a more reasonable field bridge balanced description mode to improve the scheduling efficiency of the inland river container wharf field bridge scheduling. Therefore, by optimizing and adjusting the model, the balance of the field bridge is described by the instruction number and the instruction completion time, the balance of the field bridge can be reflected more accurately, new instructions can be distributed to the field bridge more scientifically, and the scheduling efficiency of the field bridge is improved. Therefore, the parallelism and the working efficiency of the field bridge can be improved.

Description

Technical Field

[0001] The invention belongs to the technical field of logistics scheduling, and in particular relates to an inland river container terminal yard bridge scheduling method taking instruction priority into consideration. Background Art

[0002] As the main loading and unloading equipment in the container terminal yard, the dispatching result of the yard crane is the core factor affecting the overall operational efficiency of the terminal. Reasonable yard crane dispatching can not only reduce the time of ships in the port and improve customer satisfaction, but also reduce the operating costs in the yard, thereby enhancing the competitiveness of the port. With the continuous growth of container throughput in domestic inland ports, the need to improve the working efficiency of the yard cranes in inland container terminals is becoming increasingly urgent. Therefore, optimizing the dispatching method of the yard cranes in inland container terminals is of great practical significance.

[0003] Although there are many papers on container terminal crane scheduling, there are still the following limitations: (1) Existing studies have not considered the practical constraint of the priority of crane instruction execution, which is not in line with the actual situation. In the actual crane operation of inland container terminals, the sequence of instructions to be executed by the crane often contains multiple instruction types, and different instruction types, such as moving containers, loading and unloading ships, etc. Due to actual operation needs, different types of operation instructions often have different instruction execution sequence requirements. In addition, due to emergencies or equipment failures, some mandatory execution instructions or priority execution instructions often occur. Therefore, the priority of crane instruction execution should be considered in crane scheduling, which is more in line with actual application scenarios. (2) In the existing crane scheduling literature based on crane operation balance, the crane operation balance characterization method used only relies on the number of operation instructions, which is not scientific enough. In inland container terminals, there are many operational tasks such as loading and unloading of internal container trucks, picking up and returning containers by external container trucks, etc. If the balance of yard crane operations is measured only by the number of operational tasks, without considering the difficulty or completion time of each operational task, the balance of yard crane operations cannot be measured scientifically and effectively, that is, the number of yard crane operational tasks is the same, but some yard cranes complete the tasks in a short time, while some yard cranes complete the tasks in a long time.

[0004] Therefore, it is necessary to measure the balance of yard crane operation tasks not only based on the number of yard crane instructions, but also based on the type of yard crane operation instructions. This will enable a more scientific balance of tasks between yard cranes, thereby enabling the yard crane operation equipment to work in parallel for a long period of time as much as possible, thereby improving the yard efficiency. Summary of the invention

[0005] The purpose of the present invention is to provide an inland river container terminal bridge scheduling method taking instruction priority into consideration, so as to solve the problems mentioned in the background technology.

[0006] In order to achieve the above technical objectives, the technical solution adopted by the present invention is as follows:

[0007] A method for dispatching a container terminal bridge at an inland river terminal considering instruction priority, the specific steps are as follows:

[0008] Step 1: Construct and define the priority relationship of field bridge operation instructions;

[0009] Step 2: Construct a function of the number and difficulty of instructions for the busyness of the field bridge;

[0010] Step 3: Using the field bridge operation instruction priority and field bridge busyness constructed in steps 1 and 2, a new field bridge scheduling mixed integer programming model is established.

[0011] The specific method in step 1 is:

[0012] Let Q represent the set of field bridge operation instructions, assuming Q = I1∪I2…∪I s , where I s Represents a set of instructions of a certain type that satisfies (i≠j), where i, j∈{1, 2, …s}, s is the number of instruction types, and then the instruction type priority and instruction priority are defined.

[0013] The definition logic of the instruction type priority is as follows: let I and J represent two types of instruction types, let P(I) represent the execution priority of instruction type I, P(I)>P(J) means that the execution priority of instruction type I is higher than that of instruction type J, that is, type I instructions are executed first, and then type J instructions are executed;

[0014] The definition logic of the instruction priority is: let i, j∈I x , where I x Represents a certain type of instruction, x∈{1, 2, ...s}, let P(i) represent the execution priority of instruction i, P(i)>P(j) means that the execution priority of instruction i is higher than that of instruction j, that is, instruction i is executed first, and then instruction j is executed.

[0015] The specific method of step 2 is:

[0016] The busyness of the field bridge is used to characterize the balance of the field bridge. The busyness of the field bridge depends not only on the number of tasks, but also on the task type (task difficulty). That is, the busyness of the field bridge is a function of the number of instructions and the difficulty level1:

[0017]

[0018] The superscript i indicates the bridge number, B i represents the busyness of field bridge i, Represents the number of type j instructions in the instruction queue of field bridge i, represents the time required for field bridge i to complete type j instruction, C i represents the number of instruction categories in the instruction queue of field bridge i, that is, j∈{1, 2, ..., C i}, if the total number of available field bridges is E, then i∈{1, 2, ..., E};

[0019] The function f in formula 1 is defined as the weighted sum: that is, the number of instructions of each type Multiply the completion time of each type of instruction Therefore, Formula 1 can be further rewritten as:

[0020]

[0021] Among them C i Indicates the number of instruction categories in the instruction queue of field bridge i.

[0022] The specific method of step 3 is:

[0023] The existing method of balancing field bridge operation tasks is optimized. The conventional method of directly using the variance of the number of field bridge operation instructions in the objective function to characterize the balance is adjusted to use it to characterize the field bridge operation balance, and the model is constructed through the average field bridge scheduling execution time, field bridge busyness and instruction priority.

[0024] Compared with the prior art, the present invention has at least the following advantages:

[0025] 1. Introduce instruction execution priority to make the field bridge scheduling scheme more in line with the actual scenario of inland port field bridge scheduling. It should be emphasized that the introduction of instruction priority is very necessary, which will make the field bridge scheduling scheme more in line with practical applications. In actual field bridge operations, the sequence of instructions to be executed by the field bridge often contains multiple instruction types, and different instruction types have different instruction execution order requirements due to actual operation needs. In addition, due to emergencies or equipment failures, some instructions are often manually enforced or prioritized. Therefore, the priority of field bridge instruction execution should be considered in field bridge scheduling. In summary, compared with the existing field bridge scheduling method, the present invention considers the priority of field bridge instruction execution in field bridge scheduling, which is more in line with actual application scenarios.

[0026] 2. Use a more reasonable way to characterize the field bridge balance to make the field bridge operation task allocation more reasonable, and thus make the field bridge scheduling plan more efficient. In the present invention, new instructions are allocated according to the field bridge busyness, and the parallelism of the field bridge operation is improved by minimizing the variance of the field bridge busyness, thereby achieving the purpose of improving the field bridge operation efficiency. It is worth noting that the characterization of the field bridge balance used in the model established by the present invention is different from that in the existing literature. In the existing literature, the characterization of the field bridge balance is only based on the number of existing instructions in the field bridge, but in the actual operation process, the difficulty of a task of the field bridge operation is different, and the completion time is also different. Therefore, it is not scientific to only rely on the number of tasks to characterize the field bridge balance. In summary, the present invention characterizes the field bridge balance with the number of instructions and the completion time of the instructions, which can more accurately reflect the balance of the field bridge, and then can more scientifically allocate new instructions to the field bridge, thereby improving the parallelism and work efficiency of the field bridge. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The present invention is further illustrated by means of the non-limiting examples given in the accompanying drawings.

[0028] Figure 1 It is a schematic diagram of the process of the present invention.

[0029] Figure 2 This is the instruction priority relationship diagram of the present invention.

[0030] Figure 3 This is a flow chart of instruction priority of the present invention.

[0031] Figure 4 The figure is a flow chart of calculating the busyness of the field bridge of the present invention.

[0032] Figure 5 It is the flow chart of the genetic algorithm of the present invention.

[0033] Figure 6 This is the convergence process of the GA of the present invention. DETAILED DESCRIPTION

[0034] In order to enable those skilled in the art to better understand the present invention, the technical solution of the present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0035] like Figure 1-6 As shown in FIG. 1 , a method for dispatching a yard bridge of an inland container terminal considering the priority of instructions is shown in FIG. 1 . The specific steps are as follows:

[0036] Step 1: Construct and define the priority relationship of field bridge operation instructions;

[0037] Step 2: Construct a function of the number and difficulty of instructions for the busyness of the field bridge;

[0038] Step 3: Using the field bridge operation instruction priority and field bridge busyness constructed in steps 1 and 2, a new field bridge scheduling mixed integer programming model is established.

[0039] The specific method in step 1 is:

[0040] Let Q represent the set of field bridge operation instructions, assuming Q = I1∪I2…∪I s , where I s Represents a set of instructions of a certain type that satisfies (i≠j), where i, j∈{1, 2, …s}, s is the number of instruction types, and then the instruction type priority and instruction priority are defined.

[0041] The definition logic of the instruction type priority is as follows: let I and J represent two types of instruction types, let P(I) represent the execution priority of instruction type I, P(I)>P(J) means that the execution priority of instruction type I is higher than that of instruction type J, that is, type I instructions are executed first, and then type J instructions are executed;

[0042] The definition logic of the instruction priority is: let i, j∈I x , where I x Represents a certain type of instruction, x∈{1, 2, ...s}, let P(i) represent the execution priority of instruction i, P(i)>P(j) means that the execution priority of instruction i is higher than that of instruction j, that is, instruction i is executed first, and then instruction j is executed.

[0043] It can be seen from the two definition logics that if the instructions belong to different instruction types, the priority of the instructions is determined according to the priority of the instruction type; if the instructions belong to the same instruction type, the priority of the instructions is determined according to the priority of the instructions themselves.

[0044] Due to mechanical failures, temporary decisions and other reasons during the actual operation process, it is often the case that the operation instructions are subject to human decision-making, such as forced execution or priority execution. At this time, the priority of the forced execution instruction is higher than the priority of the priority execution instruction, and the priority of the priority execution instruction is higher than the priority of the non-human specified instruction.

[0045] The specific method of step 2 is:

[0046] The busyness of the field bridge is used to characterize the balance of the field bridge. The busyness of the field bridge depends not only on the number of tasks, but also on the task type (task difficulty). That is, the busyness of the field bridge is a function of the number of instructions and the difficulty level1:

[0047]

[0048] The superscript i indicates the bridge number, B irepresents the busyness of field bridge i, Represents the number of type j instructions in the instruction queue of field bridge i, represents the time required for field bridge i to complete type j instruction, C i represents the number of instruction categories in the instruction queue of field bridge i, that is, j∈{1, 2, ..., C i}, if the total number of available field bridges is E, then i∈{1, 2, ..., E};

[0049] The function f in formula 1 is defined as the weighted sum: that is, the number of instructions of each type Multiply the completion time of each type of instruction Therefore, Formula 1 can be further rewritten as Formula 2:

[0050]

[0051] Among them C i Indicates the number of instruction categories in the instruction queue of field bridge i.

[0052] The specific method of step 3 is:

[0053] Model parameter description:

[0054] e is the e-th work site bridge in the box area;

[0055] n∈[1, N] is the nth container loading and unloading task (nth container) in a batch task, and N is the total number of tasks in the batch;

[0056] α is the weight of the field bridge operation balance;

[0057] l0 is the length per unit beige;

[0058] L is the safe distance between two cranes operating simultaneously;

[0059] V is the travel speed of the field crane trolley (the field crane trolley is the traveling mechanism of the field crane, used to realize the horizontal movement of the field crane);

[0060] T0 is the time it takes for the yard crane to complete a container loading and unloading task;

[0061] B i is the busyness of field bridge i;

[0062] is the average busyness of the field bridge;

[0063] H ie is the i-th container loading and unloading task of the crane e, i∈[1,Q e ];

[0064] For task H ieThe time when the corresponding container truck arrives at the yard;

[0065] For the field bridge arrival task H ie The time corresponding to the working position;

[0066] For task H ie The moment of completion, Used to define the initial time 0 of the field bridge operation;

[0067] To complete the task H ie The corresponding field bridge idle time;

[0068] T(H (i-1)e , H ie ) is the time required for the field crane e to move to the working position of the next task after completing one task;

[0069] For task H ie The position number of the shell, B(H 0e ) is the initial position number of the field bridge e;

[0070] is the position of the field bridge e at time t, and t is any time during the operation task.

[0071] Construct model decision variables:

[0072] X ne is a 0-1 variable. If container loading and unloading task n is assigned to the yard bridge e, then X ne =1, otherwise X ne =0;

[0073] Establish objective function 3:

[0074] minZ=αf1+(1-α)f2

[0075]

[0076] f1 represents the variance of the busyness of each terminal bridge, and f2 represents the non-loading and unloading time of the terminal bridge, including the terminal bridge idle time (waiting time) and running time.

[0077] Set up constraints:

[0078] It means that each task can only be completed by one field crane;

[0079] Indicates the busyness of field bridge i;

[0080] Indicates the average busyness;

[0081] represents the time when field bridge e completes task i;

[0082] Indicates the time when the field bridge e arrives at the task i;

[0083] It represents the idle time corresponding to the completion of task i by field bridge e;

[0084] It indicates the time required for the field bridge to move from one task to the next;

[0085] It means to ensure safe working distance between the yard bridges;

[0086] The sum of the operations of each field bridge is the total operation volume;

[0087] P(I1)>P(I2)>…>P(I s ); indicates the priority of the instruction type.

[0088] In the established objective function, α is a real number ranging from 0 to 1.

[0089] It should be noted that in the prior art, in order to balance the field bridge operation tasks and improve the parallelism of the field bridge operation, the variance of the number of field bridge operation instructions is directly used in the objective function to characterize the balance. However, when multiple different types of operation instructions appear in the operation scenario, this characterization method is not applicable.

[0090] Based on this, the variance of the field bridge busyness is used in the objective function of the present invention to characterize the field bridge operation balance, where the field bridge busyness is related to both the number of field bridge operation instructions and the instruction type, that is, the busyness of field bridge i

[0091] In addition, in the objective function, when α=0, the objective function minZ=f2, which means that only the non-loading and unloading time of the field crane is concerned, that is, the goal is to optimize the idle time (waiting time) and running time of the field crane, and the main goal is to reduce the operating cost of the field crane; when α=1, the objective function minZ=f1, which means that only the variance of the field crane's busyness is concerned, that is, the goal is to balance the field crane's operating tasks and improve the parallelism of the field crane's operations; and when 0<α<1, minZ=αf1+(1-α)f2, which means that both the idle time (waiting time) and running time of the field crane are optimized and the operating tasks of the field crane are balanced.

[0092] In minZ=αf1+(1-α)f2, α can be understood as a hyperparameter. The determination of α is related to the actual operating environment and operating requirements. When the actual operating environment and operating requirements prefer to improve the parallelism of the field bridge, a larger α value can be taken. When the actual operating environment and operating requirements prefer to reduce costs, a smaller α value can be taken.

[0093] The following explains The calculation process:

[0094] It represents the average time for field bridge i to execute type j instruction, measured in seconds (s), where The same field bridge takes different time to execute different types of instructions, which reflects the difficulty of the task;

[0095] Similarly, existence That is, the same type of instructions may have different operation times on different field cranes, which reflects the operation capability of the field crane.

[0096] Assume that in a period of time, the number of instructions of type j executed by field bridge i is Q, and their execution times are marked as but The calculation formula is as follows:

[0097]

[0098] in The calculation formula is as follows:

[0099]

[0100] in Indicates the start time of the qth j-type instruction of the field bridge i instruction, It indicates the completion time of the jth instruction of the field bridge i instruction. The start time and end time are based on the system time in TOS.

[0101] According to the formula It can be seen that is the average execution time, which is obtained based on historical data statistics, that is, the average completion time of class j instructions is taken over a long period of time, such as one year. Since this average value can comprehensively reflect the performance of field bridge i in completing class j tasks, and it is easy to obtain data and facilitate calculation, it is reasonable to use it as a measure of task difficulty.

[0102] Finally, the significance of introducing the field bridge busyness and the field bridge operation instruction priority to establish a new field bridge scheduling model is explained. First, the introduction of instruction priority is very necessary, which will make the field bridge scheduling scheme more in line with practical applications. In actual field bridge operations, the sequence of instructions to be executed by the field bridge often contains multiple instruction types, and different instruction types have different instruction execution order requirements due to actual operation needs. In addition, due to emergencies or equipment failures, some instructions are often manually enforced or prioritized. Therefore, the priority of field bridge instruction execution should be considered in field bridge scheduling.

[0103] Second, in the field bridge scheduling model built by the present invention, the description of the field bridge operation balance is more scientific. In the prior art, in order to balance the field bridge operation tasks and improve the parallelism of the field bridge operation, the variance of the number of field bridge operation instructions is directly used in the objective function to describe the balance. However, when a variety of different types of operation instructions appear in the operation scene, this description cannot well achieve the maximum parallel operation of the field bridge.

[0104] Based on this, the variance of the field bridge busyness is used in the objective function of the present invention to characterize the field bridge operation balance, wherein the field bridge busyness is related to both the number of field bridge operation instructions and the instruction type.

[0105] The following is an example of applying the optimized model of the present invention to the prior art (prior art: Fan Houming, Yao Qian, Ma Mengzhi. Container yard slot allocation problem under multi-yard bridge regional balance planning [J]. Control and Decision, 2016, 31(9): 1603-1608.):

[0106] Inland port yard crane operation instructions often have different types, and the execution priorities of different operation instruction types are often different. Therefore, in order to simulate the actual inland port yard crane operation scenario, we added a new attribute, namely the instruction type, to the operation instruction (task) based on the existing technical examples, and considered the execution priority of different instruction types.

[0107] The examples are as follows:

[0108] Taking the yard crane loading and unloading task as an example, a regional balance planning mode is adopted. The initial condition is set as a yard with 40 bays, each bay has 21 storage spaces (considering the reserved container turning space), and a container terminal has 50 container loading and unloading tasks, of which there are 17 tasks of instruction type X, 18 tasks of instruction type Y, and 15 tasks of instruction type Z. The task operation time of instruction type X is 3 minutes, the task operation time of instruction type Y is 2 minutes, and the task operation time of instruction type Z is 1 minute. The destination port, type and corresponding arrival time of container trucks for each instruction are shown in Figure 5, the initial stockpile volume at each bay location and the corresponding destination port Figure 6 There are two field cranes in the box area. The working area of ​​field crane 1 is 1 to 20 bays, and the working area of ​​field crane 2 is 21 to 40 bays. The minimum safe distance between the two field cranes is 160 feet, that is, 8 bays. The length of a unit bay is 7m, and the operating speed of the field crane is 100m / min. The initial bay numbers of the two field cranes are 1 and 40 respectively, and the weight of the field crane operation balance is 0.5.

[0109] Model solution: Genetic algorithm is used. The initial population is the bay number corresponding to 50 tasks. Due to the regional division method, when the initial population is established, the bay corresponding to the task between 1 and 20 (including the endpoints) is assigned to the field bridge 1, and the bay corresponding to the task between 21 and 40 (including the endpoints) is assigned to the field bridge 2. When the initial population is established, the operation order of the field bridge corresponding to each individual is fixed. Real number coding is used in chromosome coding, so the chromosome coding reflects the container bay allocation and field bridge scheduling plan, while in the crossover and mutation operations, only the bay allocation plan is reflected. The crossover and mutation methods adopt two-point crossover and single-point mutation. Part of the data in Table 1 and Table 2 comes from the existing technology.

[0110]

[0111] Table 1: Tasks in the box area

[0112]

[0113] Table 2: Initial stockpiling of each shell position in the container area

[0114] MATLAB is used for programming and solving. The population size is set to 100, the crossover rate is 0.7, the mutation rate is 0.08, and the maximum number of iterations is 1500. As the number of iterations increases, the convergence effect of the system mean and the population mean is as follows: Figure 6 When the algorithm iterates 1500 times, the optimal value of the system converges to 29.755.

[0115] It can be seen from the examples that the field bridge scheduling optimization method considering the priority of the operation instruction proposed in the present invention is effective and can be applied to a wider range of field bridge operation scenarios than the existing literature or methods, that is, it can be applied to field bridge operation scenarios with different types of operation instructions. When the types of field bridge operation instructions are the same and the execution priorities of the operation instructions are also the same, the field bridge scheduling method of the present invention degenerates into the method in the prior art.

[0116] The above embodiments are merely illustrative of the principles and effects of the present invention, and are not intended to limit the present invention. Anyone familiar with the technology may modify or change the above embodiments without violating the spirit and scope of the present invention. Therefore, all equivalent modifications or changes made by those with ordinary knowledge in the technical field without departing from the spirit and technical ideas disclosed by the present invention should still be covered by the claims of the present invention.

Claims

1. A method for dispatching a container terminal bridge at an inland river considering instruction priority, characterized in that: The specific steps are as follows: Step 1: Construct and define the priority relationship of field bridge operation instructions; Step 2: Construct a function of the number and difficulty of instructions for the busyness of the field bridge; Step 3: Using the field bridge operation instruction priority and field bridge busyness constructed in steps 1 and 2, a new field bridge scheduling mixed integer programming model is established.

2. The method for dispatching inland river container terminal bridges considering instruction priority according to claim 1, characterized in that: The specific method in step 1 is: Let Q represent the set of field bridge operation instructions, assuming Q = I1∪I2…∪I s , where I s Represents a set of instructions of a certain type that satisfies Where i, j∈{1,,2…s}, s is the number of instruction types, and then the instruction type priority and instruction priority are defined.

3. The method for dispatching inland river container terminal bridges considering instruction priority according to claim 2, characterized in that: The definition logic of the instruction type priority is as follows: let I and J represent two types of instruction types, let P(I) represent the execution priority of instruction type I, P(I)>P(J) means that the execution priority of instruction type I is higher than that of instruction type J, that is, type I instructions are executed first, and then type J instructions are executed; The definition logic of the instruction priority is: let i, j∈I x , where I x Represents a certain type of instruction, x∈{1, 2, …s}, let P(i) represent the execution priority of instruction i, P(i)>P(j) means that the execution priority of instruction i is higher than that of instruction j, that is, instruction i is executed first, and then instruction j is executed.

4. The method for dispatching inland river container terminal bridges considering instruction priority according to claim 3 is characterized by: The specific method of step 2 is: The busyness of the field bridge is used to characterize the balance of the field bridge. The busyness of the field bridge depends not only on the number of tasks, but also on the task type (task difficulty). That is, the busyness of the field bridge is a function of the number of instructions and the difficulty level1: The superscript i indicates the bridge number, B i represents the busyness of field bridge i, Represents the number of type j instructions in the instruction queue of field bridge i, represents the time required for field bridge i to complete type j instruction, C i represents the number of instruction categories in the instruction queue of field bridge i, that is, j∈{1, 2, …, C i }, if the total number of available field bridges is E, then i∈{1, 2, …, E}; The function f in formula 1 is defined as the weighted sum: that is, the number of instructions of each type Multiply the completion time of each type of instruction Therefore, Formula 1 can be further rewritten as: Among them C i Indicates the number of instruction categories in the instruction queue of field bridge i.

5. The method for dispatching inland river container terminal bridges considering instruction priority according to claim 4, characterized in that: The specific method of step 3 is: The existing method of balancing field bridge operation tasks is optimized. The conventional method of directly using the variance of the number of field bridge operation instructions in the objective function to characterize the balance is adjusted to use it to characterize the field bridge operation balance, and the model is constructed through the average field bridge scheduling execution time, field bridge busyness and instruction priority.

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