Production order and production path production scheduling method based on ant colony algorithm

Abstract

The invention relates to the technical field of production path planning, and discloses an ant colony algorithm-based production order and production path scheduling method, which comprises the following steps of S1, obtaining order data and equipment data, constructing and initializing a pheromone matrix, and setting the size of an ant colony and the maximum number of iterations; s2, performing primary iteration of the ant colony based on the order data and the pheromone matrix; s3, updating a pheromone matrix based on a production path explored by each ant in the ant colony and a fitness function; s4, repeating the steps S2-S3 until the maximum number of iterations is reached; s5, obtaining a production path with the highest fitness in all iterations as an optimal production path, and outputting a production plan table and a corresponding equipment plan Gantt chart; according to the invention, by introducing the improved ant colony algorithm and combining actual production constraints, efficient, flexible and low-cost production scheduling is provided for order production, and the efficiency of order production is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of production path planning, and in particular to a production order and production path scheduling method based on ant colony algorithm. Background Art

[0002] At present, more and more intelligent optimization algorithms are being applied to the field of production scheduling to improve the efficiency and quality of production scheduling, such as genetic algorithms, simulated annealing algorithms, particle swarm optimization algorithms, etc., but there are still some shortcomings that need to be improved and perfected. In the actual production environment, conditions such as order demand and equipment status may change, while general optimization algorithms usually assume that the environment is static and unchanged, which makes it difficult for the algorithm to cope with emergencies. In large-scale production systems, a large amount of computing resources will be consumed in the iteration process, which places high demands on the enterprise's IT infrastructure. Many existing algorithm models focus on theoretical optimization goals, such as minimizing the production cycle or maximizing equipment utilization, but ignore some important constraints in actual production, such as equipment maintenance plans, human resource constraints, etc.

[0003] For example, a Chinese patent with authorization announcement number CN112966876B discloses a production scheduling method, device, electronic device and readable medium for orders, the method comprising: obtaining pending orders; assigning the pending orders to a target queue according to the target execution time of the pending orders; when processing the pending orders in the target queue according to the priority information of the target queue, determining the production path of the pending orders according to the capacity information of the node to be selected at the current moment; and producing the pending orders according to the production path. The production scheduling method, device, electronic device and readable medium for orders provided by the invention can shorten the production cycle of orders and make the use of warehouse capacity more reasonable, but there are still problems raised by the background technology, ignoring the constraints in actual production, such as equipment maintenance plans, etc., making the method difficult to deal with emergencies.

[0004] The information disclosed in this background technology section is only intended to enhance the understanding of the overall background of the invention and should not be regarded as an acknowledgement or any form of suggestion that the information constitutes the prior art already known to ordinary technicians in this field. Summary of the invention

[0005] The technical problem to be solved by the present invention is to overcome the defects of the prior art and provide a production order and production path scheduling method based on ant colony algorithm. By introducing an improved ant colony algorithm and combining it with actual production constraints, efficient, flexible and low-cost production scheduling is provided for production orders, which helps to improve the efficiency of order production.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] A production order and production path scheduling method based on ant colony algorithm, comprising the following steps:

[0008] S1: Obtain order data and equipment data, build and initialize the pheromone matrix, set the ant colony size and the maximum number of iterations;

[0009] S2: performing an iteration of the ant colony based on the order data and the pheromone matrix;

[0010] S3: updating the pheromone matrix based on the production path explored by each ant in the ant colony and the fitness function;

[0011] S4: Repeat steps S2-S3 until the maximum number of iterations is reached;

[0012] S5: Obtain the production path with the highest fitness among all iterations as the optimal production path, and output a production schedule and a corresponding equipment plan Gantt chart based on the optimal production path.

[0013] As a preferred solution of the production order and production path scheduling method based on ant colony algorithm of the present invention, wherein: the order data includes the order number of each order, the delivery deadline, and all the processes included in each order and the execution order of the processes, the equipment corresponding to each process and the standard working time of each process;

[0014] The equipment data includes the equipment code of each equipment and the equipment maintenance plan; wherein, the equipment code includes the equipment type and equipment number; the equipment maintenance plan includes the equipment code to be maintained and the maintenance start time and maintenance duration of each equipment to be maintained; the pheromone matrix is ​​a matrix of N rows and N columns, wherein N represents the number of orders to be completed; the elements in the ath row and bth column of the pheromone matrix represent the pheromone concentration between directed paths ab; the directed path ab represents selecting the bth order after selecting the ath order; each element in the initialized pheromone matrix is ​​equal.

[0015] As a preferred solution of the production order and production path scheduling method based on ant colony algorithm of the present invention, wherein: the production path represents an order sequence composed of orders in the order of execution; the complete production path is a production path containing all orders to be executed;

[0016] The method for performing an iteration of the ant colony is as follows:

[0017] S201: Initialize the taboo table and equipment plan Gantt chart for each ant;

[0018] S202: randomly select an order as the current order for each ant and calculate the completion time of the current order;

[0019] S203: updating the taboo table and equipment plan Gantt chart for each ant;

[0020] S204: selecting a next order for each ant based on the pheromone matrix;

[0021] S205: Repeat steps S203-S204 until each ant has explored a complete production path.

[0022] As a preferred solution of the production order and production path scheduling method based on ant colony algorithm of the present invention, wherein: the taboo table includes a completion area and an occupied area, and during the iteration process, the orders in the taboo table cannot be selected; the method for initializing the taboo table for any ant is to fill the occupied area, and the method is as follows:

[0023] Calculate the completion time of each order outside the taboo list, the formula is as follows:

[0024] ;

[0025] in, Indicates the completion time of any order; Indicates the current moment; Indicates the equipment waiting time corresponding to the i-th process of the order; Indicates the standard working time of the i-th process; the value range of i is 1, 2, ..., M, where M is the number of processes included in the order; if the completion time of any order A is later than the start time of the maintenance of the equipment involved in the order, then order A will be added to the occupied area; the processes of any order are executed in sequence, that is, the next adjacent process will be executed after the previous process is completed;

[0026] The equipment waiting time is the time difference between the start time of the process and the start time of the equipment being available, and if the start time of the equipment being available is no later than the start time of the corresponding process, the equipment waiting time is 0; if the equipment is under maintenance, the start time of the equipment being available is calculated as the start time of the maintenance plus the maintenance duration; otherwise, the start time of the equipment being available is calculated as the start time of the previous process executed by the equipment plus the standard working time of the previous process executed by the equipment.

[0027] As a preferred solution of the production order and production path scheduling method based on ant colony algorithm described in the present invention, the equipment planning Gantt chart is used to represent the working time and idle time of each equipment; the initialization method is as follows: in the equipment planning Gantt chart, a vertical coordinate is assigned to all equipment, and the horizontal coordinate is time; each process being executed is drawn in the equipment planning Gantt chart, the vertical coordinate is the equipment corresponding to the process, the starting point of the horizontal coordinate is the current time, and the end point of the horizontal coordinate is the current time plus the remaining working time of the process, and the process name is marked on the equipment planning Gantt chart.

[0028] As a preferred solution of the production order and production path scheduling method based on ant colony algorithm of the present invention, the method of updating the taboo table and equipment plan Gantt chart for each ant is as follows:

[0029] S2031: adding each process included in the current order to the equipment plan Gantt chart; wherein the starting point of the horizontal axis is the start time when the equipment corresponding to the process is available; and the end point of the horizontal axis is the starting point plus the standard working time of the process;

[0030] S2032: remove the order in the occupied area in the taboo list from the taboo list;

[0031] S2033: Add the current order to the completion area of ​​the taboo list;

[0032] S2034: Fill the occupied area of ​​the taboo table.

[0033] As a preferred solution of the production order and production path scheduling method based on ant colony algorithm of the present invention, the method of selecting the next order for each ant is as follows:

[0034] S2041: Calculate the probability that the ant chooses any order as the next order. The formula is as follows:

[0035] ;

[0036] Among them, D represents the current order, B and C both represent the collection Any order in ; where the set Includes all orders outside the taboo list; represents the probability of selecting order B as the next order; represents the pheromone concentration on the directed path DB, It represents the pheromone concentration on the directed path DC, which is obtained based on the pheromone matrix; Represents the heuristic factor on the directed path DB; Represents the heuristic factor on the directed path DC; It is a pheromone regulatory factor;

[0037] S2042: Determine the next order to be selected by a roulette algorithm based on the probability that the ant selects each order as the next order;

[0038] S2043: Update the current order to the next selected order.

[0039] As a preferred solution of the production order and production path scheduling method based on ant colony algorithm described in the present invention, the calculation formula of the heuristic factor is as follows:

[0040] ;

[0041] in, Indicates the total number of devices involved in order D; Indicates the number of devices involved in both order D and order C;

[0042] The expression of the pheromone regulatory factor is as follows:

[0043]

[0044] Where n represents the current iteration number; is the maximum number of iterations.

[0045] As a preferred solution of the production order and production path scheduling method based on ant colony algorithm of the present invention, the formula of the fitness function is as follows:

[0046] ;

[0047] Among them, H represents the fitness of any production path; , , All are weight coefficients; Indicates the completion time of the last order in the production path; represents the number of normal orders in the production path, where the normal orders are orders whose completion time is earlier than the delivery deadline; represents the number of overdue orders in the production path, where the overdue orders are orders whose completion time is not earlier than the delivery deadline; represents the delivery deadline of the jth normal order; represents the order completion time of the jth normal order; represents the delivery deadline of the kth overdue order; Indicates the order completion time of the kth overdue order.

[0048] As a preferred solution of the production order and production path scheduling method based on ant colony algorithm of the present invention, the method for updating the pheromone matrix is ​​as follows:

[0049] Calculate the fitness of each production path obtained in this iteration and sort them, and select the m production paths with the highest fitness as reference paths, where m is a positive integer; update each element in the pheromone matrix, and the formula is as follows:

[0050] ;

[0051] in, represents the concentration of any pheromone in the pheromone matrix in this round of iteration; EF is The corresponding directed path; express Updated value; represents the pheromone concentration left by the ants corresponding to the p-th reference path between the directed paths EF in this iteration. If the p-th reference path does not contain the directed path EF, then The value is 0; otherwise, The calculation formula is as follows:

[0052] ;

[0053] in, Indicates the fitness of the pth reference path in this iteration; Indicates the highest fitness of the m production paths in this iteration;

[0054] is the volatility coefficient of pheromone, and the calculation formula is as follows:

[0055] ;

[0056] in, Indicates the highest fitness of all production paths up to this iteration.

[0057] Compared with the prior art, the beneficial effects achieved by the present invention are as follows:

[0058] By effectively managing the working time and idle time of equipment, the present invention helps to improve equipment utilization, and the scheme helps to shorten the production cycle and improve overall production efficiency. The present invention can better adapt to changes in the production environment, such as changes in equipment maintenance plans, thereby making production scheduling more flexible.

[0059] By minimizing the total time cost of the production path, this solution can accurately predict the order completion time, reduce order overdue situations, and improve customer satisfaction. Automated scheduling reduces the reliance on manual scheduling and reduces the risk of production delays caused by human errors. By comprehensively considering multiple production constraints, this solution improves the scheduling plan's ability to adapt to various uncertainties in actual production.

[0060] Through the dynamic adjustment of pheromone volatility coefficient and the application of genetic algorithm strategy, this scheme can accelerate the convergence speed of the algorithm and reduce the calculation time to a certain extent. The output production schedule and equipment plan Gantt chart enable production managers to intuitively understand the entire production process, which is convenient for monitoring and management. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0062] Figure 1 A flowchart of the production order and production path scheduling method based on the ant colony algorithm provided by the present invention;

[0063] Figure 2 A flow chart of a method for updating a taboo table and an equipment plan Gantt chart provided by the present invention;

[0064] Figure 3 A flow chart of the method for selecting the next order provided by the present invention. DETAILED DESCRIPTION

[0065] The technical solution of the present invention is described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solution of the present invention, rather than limitations on the technical solution of the present invention. The embodiments of the present invention and the technical features in the embodiments may be combined with each other unless there is a conflict.

[0066] This embodiment introduces a production order and production path scheduling method based on ant colony algorithm. Figure 1 , the method comprises the following steps:

[0067] S1: Obtain order data and equipment data, build and initialize the pheromone matrix, set the ant colony size and the maximum number of iterations;

[0068] The order data includes the order number and delivery deadline of each order, as well as all processes included in each order and the execution order of the processes, the equipment corresponding to each process and the standard working time of each process;

[0069] The equipment data includes the equipment code of each equipment and the equipment maintenance plan; wherein, the equipment code includes the equipment type and equipment number; the equipment maintenance plan includes the equipment code to be maintained and the maintenance start time and maintenance duration of each equipment to be maintained; the pheromone matrix is ​​a matrix of N rows and N columns, wherein N represents the number of orders to be completed; the elements in the ath row and bth column of the pheromone matrix represent the pheromone concentration between directed paths ab; the directed path ab represents selecting the bth order after selecting the ath order; each element in the initialized pheromone matrix is ​​equal.

[0070] S2: performing an iteration of the ant colony based on the order data and the pheromone matrix; when each ant in the ant colony explores a complete production path, the iteration of the ant colony is completed;

[0071] The production path represents a sequence of orders in the order of execution; a complete production path is a production path that includes all orders to be executed;

[0072] The method for performing an iteration of the ant colony is as follows:

[0073] S201: Initialize the taboo table and equipment plan Gantt chart for each ant;

[0074] The taboo table includes a completion area and an occupied area. During the iteration process, the orders in the taboo table cannot be selected. The method for initializing the taboo table for any ant is to fill the occupied area as follows:

[0075] Calculate the completion time of each order outside the taboo list, the formula is as follows:

[0076] ;

[0077] in, Indicates the completion time of any order; Indicates the current moment; Indicates the equipment waiting time corresponding to the i-th process of the order; Indicates the standard working time of the i-th process; the value range of i is 1, 2, ..., M, where M is the number of processes included in the order; if the completion time of any order A is later than the start time of the maintenance of the equipment involved in the order, then order A will be added to the occupied area; the processes of any order are executed in sequence, that is, the next adjacent process will be executed after the previous process is completed;

[0078] The equipment waiting time is the time difference between the start time of the process and the start time of the equipment being available, and if the start time of the equipment being available is not later than the corresponding process start time, the equipment waiting time is 0; if the equipment is under maintenance, the calculation method of the start time of the equipment being available is the maintenance start time plus the maintenance duration; otherwise, the calculation method of the start time of the equipment being available is the start time of the previous process executed by the equipment plus the standard working time of the previous process executed by the equipment;

[0079] The equipment plan Gantt chart is used to represent the working time and idle time of each equipment; the initialization method is as follows: in the equipment plan Gantt chart, a vertical coordinate is assigned to all equipment, and the horizontal coordinate is time; each process being executed is drawn in the equipment plan Gantt chart, the vertical coordinate is the equipment corresponding to the process, the starting point of the horizontal coordinate is the current time, and the end point of the horizontal coordinate is the current time plus the remaining working time of the process, and the process name is marked on the equipment plan Gantt chart;

[0080] S202: randomly select an order as the current order for each ant and calculate the completion time of the current order;

[0081] S203: Update the taboo table and equipment plan Gantt chart for each ant. Refer to Figure 2 , as follows:

[0082] S2031: adding each process included in the current order to the equipment plan Gantt chart; wherein the starting point of the horizontal axis is the start time when the equipment corresponding to the process is available, indicating the start time of the process; the end point of the horizontal axis is the starting point plus the standard working time of the process, indicating the completion time of the process;

[0083] S2032: remove the order in the occupied area in the taboo list from the taboo list;

[0084] S2033: Add the current order to the completion area of ​​the taboo list;

[0085] S2034: Filling the occupied area of ​​the taboo table;

[0086] S204: Select the next order for each ant based on the pheromone matrix. The method is as follows Figure 3 , as follows:

[0087] S2041: Calculate the probability that the ant chooses any order as the next order. The formula is as follows:

[0088] ;

[0089] Among them, D represents the current order, B and C both represent the collection Any order in ; where the set Includes all orders outside the taboo list; represents the probability of selecting order B as the next order; represents the pheromone concentration on the directed path DB, It represents the pheromone concentration on the directed path DC, which is obtained based on the pheromone matrix; Represents the heuristic factor on the directed path DB; Represents the heuristic factor on the directed path DC; the calculation formula is as follows:

[0090] ;

[0091] in, Indicates the total number of devices involved in order D; Indicates the number of devices involved in both order D and order C. If the number of devices involved in both the current order D and any order C to be selected is large, the execution of order C will inevitably be affected by order D. Multiple devices involved in order C have waiting time. Therefore, the execution efficiency of order C is low, and the selection probability of order C should be reduced.

[0092] is the pheromone regulatory factor, and its expression is as follows:

[0093]

[0094] Where n represents the current iteration number; is the maximum number of iterations; as the number of iterations increases, the pheromone regulation factor gradually increases , increase the guiding effect of pheromones;

[0095] S2042: Determine the next order to be selected by a roulette algorithm based on the probability that the ant selects each order as the next order;

[0096] S2043: Update the current order to the next selected order;

[0097] S205: Repeat steps S203-S204 until each ant has explored a complete production path;

[0098] S3: updating the pheromone matrix based on the production path explored by each ant in the ant colony and the fitness function;

[0099] The formula of the fitness function is as follows:

[0100] ;

[0101] Among them, H represents the fitness of any production path; , , They are all weight coefficients, which are set by technicians in this field based on actual needs; Indicates the completion time of the last order in the production path; represents the number of normal orders in the production path, where the normal orders are orders whose completion time is earlier than the delivery deadline; represents the number of overdue orders in the production path, where the overdue orders are orders whose completion time is not earlier than the delivery deadline; represents the delivery deadline of the jth normal order; represents the order completion time of the jth normal order; represents the delivery deadline of the kth overdue order; represents the order completion time of the kth overdue order;

[0102] The first summation term in the fitness function formula is the total time cost of the production path. The earliest time to complete all orders, the higher the fitness, and the ant colony is encouraged to explore the production path with the lowest total time cost; the second summation term is the reward term for completing orders ahead of schedule. The higher the cumulative sum of the early completion time of each order, the higher the fitness of the production path, and the ant colony is encouraged to explore a production path in which all orders can be delivered ahead of schedule; the third summation term is the penalty term for overdue orders. The longer the cumulative overdue time of the orders, the lower the fitness of the production path, and the ant colony is encouraged to explore a production path that does not generate overdue orders.

[0103] The method for updating the pheromone matrix is ​​as follows:

[0104] Calculate the fitness of each production path obtained in this iteration and sort them, and select the m production paths with the highest fitness as reference paths, where m is a positive integer; update each element in the pheromone matrix, and the formula is as follows:

[0105] ;

[0106] in, represents the concentration of any pheromone in the pheromone matrix in this round of iteration; EF is The corresponding directed path; express Updated value; represents the pheromone concentration left by the ants corresponding to the p-th reference path between the directed paths EF in this iteration. If the p-th reference path does not contain the directed path EF, then The value is 0; otherwise, The calculation formula is as follows:

[0107] ;

[0108] in, Indicates the fitness of the pth reference path in this iteration; Indicates the highest fitness of the m production paths in this iteration;

[0109] is the volatility coefficient of pheromone, and the calculation formula is as follows:

[0110] ;

[0111] in, It represents the highest fitness of all production paths up to this iteration. As the number of iterations increases, the volatility coefficient of pheromone gradually decreases, enhancing the guiding role of pheromone. The volatility coefficient of pheromone is numerically adjusted according to the highest fitness of the production path explored by the ant colony. The larger the highest fitness of this iteration, the smaller the volatility coefficient, which increases the inspiration of pheromone in subsequent iterative planning and promotes rapid convergence of the algorithm.

[0112] S4: Repeat steps S2-S3 until the maximum number of iterations is reached;

[0113] After each iteration, all pheromones will evaporate partially, in order to simulate the real pheromone evaporation process and prevent the pheromone on some paths from being too high and causing local optimal solutions; the "elite retention" strategy in the genetic algorithm is adopted, that is, the pheromones corresponding to which paths should be strengthened are determined according to the fitness value. A certain number (m) of high fitness solutions are selected, and the pheromone update rules are adjusted according to them. For each selected solution, the pheromone concentration is increased in proportion to its fitness value to guide more ants to choose the paths corresponding to these high-quality solutions in future iterations.

[0114] S5: Obtain the production path with the highest fitness among all iterations as the optimal production path, and output a production schedule and a corresponding equipment plan Gantt chart based on the optimal production path.

[0115] The output data of the present invention can be used to draw various production charts to prove the advancement and effectiveness of the production scheduling plan, and intuitively display the delivery date and production path of new orders; for example, retain the equipment plan Gantt chart drawn in the process of exploring the best production path to show the expected work plan of each equipment; generate a production schedule, listing the delivery deadline of each order and the start time, expected completion time, and equipment involved of each process to guide the orderly execution of production orders.

[0116] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0117] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present invention, ordinary technicians in this field can also make many forms without departing from the purpose and scope of protection of the present invention, which are all within the protection of the present invention.

Claims

1. A production order and production path scheduling method based on ant colony algorithm, characterized in that: The following steps are involved: S1: Obtain order data and equipment data, build and initialize the pheromone matrix, set the ant colony size and the maximum number of iterations; S2: performing an iteration of the ant colony based on the order data and the pheromone matrix; S3: updating the pheromone matrix based on the production path explored by each ant in the ant colony and the fitness function; S4: Repeat steps S2-S3 until the maximum number of iterations is reached; S5: Obtain the production path with the highest fitness among all iterations as the optimal production path, and output a production schedule and a corresponding equipment plan Gantt chart based on the optimal production path.

2. The method for scheduling production orders and production paths based on ant colony algorithm according to claim 1, characterized in that: The order data includes the order number and delivery deadline of each order, as well as all processes included in each order and the execution order of the processes, the equipment corresponding to each process, and the standard working time of each process; The equipment data includes the equipment code of each equipment and the equipment maintenance plan; wherein, the equipment code includes the equipment type and equipment number; the equipment maintenance plan includes the equipment code to be maintained and the maintenance start time and maintenance duration of each equipment to be maintained; the pheromone matrix is ​​a matrix of N rows and N columns, wherein N represents the number of orders to be completed; the elements in the ath row and bth column of the pheromone matrix represent the pheromone concentration between directed paths ab; the directed path ab represents selecting the bth order after selecting the ath order; each element in the initialized pheromone matrix is ​​equal.

3. The method for scheduling production orders and production paths based on ant colony algorithm according to claim 2, characterized in that: The production path represents a sequence of orders in the order of execution; a complete production path is a production path that includes all orders to be executed; The method for performing an iteration of the ant colony is as follows: S201: Initialize the taboo table and equipment plan Gantt chart for each ant; S202: randomly select an order as the current order for each ant and calculate the completion time of the current order; S203: updating the taboo table and equipment plan Gantt chart for each ant; S204: selecting a next order for each ant based on the pheromone matrix; S205: Repeat steps S203-S204 until each ant has explored a complete production path.

4. The method for scheduling production orders and production paths based on ant colony algorithm according to claim 3, characterized in that: The taboo table includes a completion area and an occupied area. During the iteration process, the orders in the taboo table cannot be selected. The method for initializing the taboo table for any ant is to fill the occupied area as follows: Calculate the completion time of each order outside the taboo list, the formula is as follows: ； in, Indicates the completion time of any order; Indicates the current moment; Indicates the equipment waiting time corresponding to the i-th process of the order; Indicates the standard working time of the i-th process; the value range of i is 1, 2, ..., M, where M is the number of processes included in the order; if the completion time of any order A is later than the start time of the maintenance of the equipment involved in the order, then order A will be added to the occupied area; the processes of any order are executed in sequence, that is, the next adjacent process will be executed after the previous process is completed; The equipment waiting time is the time difference between the start time of the process and the start time of the equipment being available, and if the start time of the equipment being available is no later than the start time of the corresponding process, the equipment waiting time is 0; if the equipment is under maintenance, the start time of the equipment being available is calculated as the start time of the maintenance plus the maintenance duration; otherwise, the start time of the equipment being available is calculated as the start time of the previous process executed by the equipment plus the standard working time of the previous process executed by the equipment.

5. The method for scheduling production orders and production paths based on ant colony algorithm according to claim 4, characterized in that: The equipment plan Gantt chart is used to represent the working time and idle time of each equipment; the initialization method is as follows: in the equipment plan Gantt chart, a vertical coordinate is assigned to all equipment, and the horizontal coordinate is time; each process being executed is drawn in the equipment plan Gantt chart, the vertical coordinate is the equipment corresponding to the process, the starting point of the horizontal coordinate is the current time, and the end point of the horizontal coordinate is the current time plus the remaining working time of the process, and the process name is marked on the equipment plan Gantt chart.

6. The method for scheduling production orders and production paths based on ant colony algorithm according to claim 5, characterized in that: The method for updating the taboo table and the equipment plan Gantt chart for each ant is as follows: S2031: adding each process included in the current order to the equipment plan Gantt chart; wherein the starting point of the horizontal axis is the start time when the equipment corresponding to the process is available; and the end point of the horizontal axis is the starting point plus the standard working time of the process; S2032: remove the order in the occupied area in the taboo list from the taboo list; S2033: Add the current order to the completion area of ​​the taboo list; S2034: Fill the occupied area of ​​the taboo table.

7. The method for scheduling production orders and production paths based on ant colony algorithm according to claim 6, characterized in that: The method for selecting the next order for each ant is as follows: S2041: Calculate the probability that the ant chooses any order as the next order. The formula is as follows: ； Among them, D represents the current order, B and C both represent the collection Any order in ; where the set Includes all orders outside the taboo list; represents the probability of selecting order B as the next order; represents the pheromone concentration on the directed path DB, It represents the pheromone concentration on the directed path DC, which is obtained based on the pheromone matrix; Represents the heuristic factor on the directed path DB; Represents the heuristic factor on the directed path DC; It is a pheromone regulatory factor; S2042: Determine the next order to be selected by a roulette algorithm based on the probability that the ant selects each order as the next order; S2043: Update the current order to the next selected order.

8. The method for scheduling production orders and production paths based on ant colony algorithm according to claim 7, characterized in that: The calculation formula of the heuristic factor is as follows: ； in, Indicates the total number of devices involved in order D; Indicates the number of devices involved in both order D and order C; The expression of the pheromone regulatory factor is as follows: ； Where n represents the current iteration number; is the maximum number of iterations.

9. The method for scheduling production orders and production paths based on ant colony algorithm according to claim 8, characterized in that: The formula of the fitness function is as follows: ； Among them, H represents the fitness of any production path; , , All are weight coefficients; Indicates the completion time of the last order in the production path; represents the number of normal orders in the production path, where the normal orders are orders whose completion time is earlier than the delivery deadline; represents the number of overdue orders in the production path, where the overdue orders are orders whose completion time is not earlier than the delivery deadline; represents the delivery deadline of the jth normal order; represents the order completion time of the jth normal order; represents the delivery deadline of the kth overdue order; Indicates the order completion time of the kth overdue order.

10. The method for scheduling production orders and production paths based on ant colony algorithm according to claim 9, characterized in that: The method for updating the pheromone matrix is ​​as follows: Calculate the fitness of each production path obtained in this iteration and sort them, and select the m production paths with the highest fitness as reference paths, where m is a positive integer; update each element in the pheromone matrix, and the formula is as follows: ； in, represents the concentration of any pheromone in the pheromone matrix in this round of iteration; EF is The corresponding directed path; express Updated value; represents the pheromone concentration left by the ants corresponding to the p-th reference path between the directed paths EF in this iteration. If the p-th reference path does not contain the directed path EF, then The value is 0; otherwise, The calculation formula is as follows: ； in, Indicates the fitness of the pth reference path in this iteration; Indicates the highest fitness of the m production paths in this iteration; is the volatility coefficient of pheromone, and the calculation formula is as follows: ； in, Indicates the highest fitness of all production paths up to this iteration.

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