Production scheduling method and system

Abstract

The invention discloses a production scheduling method and system, and the method comprises the steps: dividing a production project into a plurality of production steps according to a product production path, and each production step comprises a plurality of production lines; constructing a corresponding scheduling model based on the production lines, and performing production line pre-solving on the production scheduling of each production line by using the scheduling model; on the basis of a production line pre-solving scheme, a damage operator is introduced to carry out damage adjustment on an equipment conflict problem, then a repair operator is added to carry out repair adjustment on a solution scheme after damage adjustment, and damage adjustment and repair adjustment are continuously iterated until the optimal production scheduling result of all production lines meeting the total product amount requirement is determined. According to the method, the scheduling model is constructed by taking the production line as granularity, the scheduling solving complexity in the production line is reduced by simplifying reservoir constraints, the self-adaptive large neighborhood search algorithm is introduced to carry out iterative optimization on production line pre-solving, and a feasible solution of a single-step production scheduling problem with relatively high complexity is quickly found in finite time.

Description

Technical Field

[0001] The present invention relates to the technical field of production scheduling, and specifically relates to a production scheduling method and system. Background Art

[0002] When performing production scheduling for production projects with high complexity, usually the project is first split into multiple production projects according to business types, and then the production project with high complexity is split into multiple production processes. In each production process, resources are allocated according to production requirements and replacement iteration is performed before scheduling, so as to gradually reduce the complexity to find a feasible solution, solving the problems that cannot be solved by large-scale scheduling systems. However, if there is still a problem that the complexity of a single project and a single step is too high to be solved, it is still difficult to find a feasible solution within a limited time.

[0003] Patent document CN116187534A discloses a production scheduling method and system, which uses the method of project disassembly and replacement strategy, and the way of multi-thread parallel processing to process the whole business to obtain a better solution, but it is still difficult to optimize the scheduling problem of a single project and a single step.

[0004] Based on the above technical problems, the applicant proposes the technical solution of this application. Summary of the Invention

[0005] In order to achieve the above object, the present invention discloses a production scheduling method, including the following steps:

[0006] Split the production project according to the product production path to form multiple production steps, and each production step includes multiple production lines;

[0007] Build a corresponding scheduling model based on the production line, and use the scheduling model to perform pre-solution of the production line for the production scheduling of each production line;

[0008] Add a disruption operator based on the solution obtained from the pre-solution of the production line, perform disruption adjustment on the equipment conflict problem in the solution, and then add a repair operator to perform repair adjustment on the solution after disruption adjustment. Continuously iterate the disruption adjustment and repair adjustment until the optimal production scheduling results of all production lines that meet the total product demand are determined.

[0009] Preferably, the building a corresponding scheduling model based on the production line includes the following steps:

[0010] Define constants of consumables, consumption quantity, output products, output quantity, delivery date, and production equipment utilization rate;

[0011] Define time variables, allocation variables, and demand existence variables;

[0012] Define allocation constraints, resource constraints, and reservoir constraints;

[0013] Define the production line delivery time, production equipment utilization rate, and production equipment consumption.

[0014] Preferably, define batch variables on each production line, and the batch production output corresponding to each batch variable;

[0015] Let the total product demand satisfy the following formula:

[0016]

[0017] where tol A represents the total product demand for Product A, n A represents the number of production lines of Product A, bch A,i represents the number of batches of Product A on the i-th production line, p A,i represents the production output in a single batch of Product A, and int() represents converting the judgment condition into an integer operation.

[0018] Preferably, limit the value range of the batch variables on each production line, and the value range is: where k represents, 1 ≤ k ≤ n A ;

[0019] Let the reservoir constraint be ignored in the scheduling model, and on each production line, perform pre-solving for the production line for each batch variable within the value range.

[0020] Preferably, for the case where Product A is consumed during the production of Product B, in order to maintain the feeding balance between Product A and Product B, define the reservoir constraint as:

[0021]

[0022] where Product A has n A production lines, the i-th production line has a total of bch A,i batches, the production output per batch is p A,i , the start time of each batch is start A,i , the single-batch time is d A,i ; Product B has n B production lines, the i-th production line has a total of bch B,i batches, the consumption output per batch is p B,i , the start time is start B,i , the single-batch time is d B,i , set bch A,i , bch B,i , start A,i , start B,i are all variables, d A,i 、d B,iis a constant;

[0023] Keep the judgment condition in the above formula unchanged, and simplify the value range of the constraint time point t to the start time and end time of each production line.

[0024] Preferably, the destruction operator includes a vertical destruction operator and a horizontal destruction operator. The vertical destruction operator divides the scheduling period in the pre-solution of the production line into multiple vertical domains according to a preset time granularity based on the time window for destruction adjustment, and the horizontal destruction operator divides the scheduling plan in the pre-solution of the production line into different horizontal domains based on the production line for destruction adjustment.

[0025] Preferably, in the adjustment process of the destruction operator and the repair operator, an adaptive large neighborhood search algorithm is used to select each operator for iterative use.

[0026] The present invention also discloses a production scheduling system, including:

[0027] A production line splitting module, configured to split a production project according to a product production path to form multiple production steps, and each production step includes multiple production lines;

[0028] A pre-solution module, configured to construct a corresponding scheduling model based on the production line, and use the scheduling model to perform pre-solution of the production line scheduling for each production line;

[0029] An optimization module, configured to add a destruction operator to the solution obtained from the pre-solution of the production line, perform destruction adjustment on the equipment conflict problem in the solution, and then add a repair operator to perform repair adjustment on the solution after the destruction adjustment, and continuously iterate the destruction adjustment and the repair adjustment until the optimal production line scheduling result that meets the total product demand is determined.

[0030] The present invention also discloses a production scheduling device, including at least one processor; a memory coupled to the at least one processor, where the memory stores executable instructions, and the executable instructions, when executed by the at least one processor, cause the steps of the above method to be implemented.

[0031] The present invention also discloses a chip, including a processor, configured to call and run a computer program from a memory, so that a device installed with the chip executes the steps of the above method.

[0032] Compared with the prior art, the present invention has the following beneficial effects:

[0033] The production scheduling method provided by the present invention splits a production project into multiple production steps, and then splits each production step into multiple production lines. A scheduling model is constructed with the production line as the granularity. By simplifying the reservoir constraint, the complexity of scheduling solution in the production line is reduced. An adaptive large neighborhood search algorithm is introduced to iteratively optimize the pre-solution of the production line, so as to quickly find a feasible solution to the production scheduling problem with high complexity in a single step within a limited time.

[0034] The concept, specific structure and technical effects of the present invention will be further described below in conjunction with the accompanying drawings to fully understand the purpose, features and effects of the present invention. Description of the Drawings

[0035] Figure 1 It is a schematic flowchart of the production scheduling method of the present invention. Detailed Embodiments

[0036] In order to make the technical means, creative features, achieved purposes and effects of the invention easy to understand, the present invention will be further described below in conjunction with specific illustrations. However, the present invention is not limited to the following implemented cases.

[0037] It should be noted that the structures, proportions, sizes, etc. shown in the drawings of this specification are only used to cooperate with the content disclosed in the specification for those skilled in this technology to understand and read, and are not used to limit the limited conditions under which the present invention can be implemented. Therefore, they do not have any technical substance. Any modification of the structure, change of the proportional relationship or adjustment of the size should still fall within the scope that can be covered by the technical content disclosed by the present invention without affecting the effects that the present invention can produce and the purposes that can be achieved.

[0038] The first embodiment of the present invention discloses a production scheduling method, which is mainly for the production scheduling of compounds. In the actual production process, it is necessary to perform production scheduling according to the synthesis path of the compound, and carefully sort out the complete synthesis steps of each compound from raw materials to finished products to determine the sequence and dependency relationship between each step. Each compound contains multiple kettle requirements. The kettle requirements of each compound at different synthesis stages are decomposed, including information such as the type, quantity and usage time of the reaction kettle, etc. Then, data modeling for production scheduling is carried out. It is necessary to arrange resource allocation and time interval setting for each kettle requirement. Resource allocation is to allocate the corresponding reaction kettle resources for each requirement according to the kettle requirements, considering factors such as the specifications and available time of the reaction kettle, and establish a resource allocation model to match the reaction kettle with the kettle requirements. Time interval setting is to plan a reasonable time interval for each kettle requirement, and determine the start time and end time of each kettle requirement in combination with the sequence of the synthesis path and the time required for each step.

[0039] After data modeling, it is necessary to set constraints to detect and adjust conflicts in production scheduling, which usually include resource usage conflicts and equipment usage conflicts. Resource usage conflicts mainly check whether there are multiple kettle usage requirements competing for the same reactor resource within the same time period. If there are conflicts, they can be resolved by adjusting the time interval, replacing the reactor, or optimizing the synthesis order, etc. Equipment usage conflicts mainly consider conflicts in the usage of reactors, conveying pipelines, separation equipment, etc. During the production scheduling process, it is necessary to continuously adjust resource usage conflicts and equipment usage conflicts in production. Especially for production steps with higher complexity, it is necessary to continuously optimize and adjust the production scheduling results to meet the project delivery date as early as possible, improve equipment utilization rate, and enhance production efficiency.

[0040] As Figure 1 shown, a production scheduling method includes the following steps:

[0041] Step S1, splitting the production project according to the product production path to form multiple production steps, and each production step includes multiple production lines.

[0042] The production of compounds is planned step by step according to their synthesis paths. By the synthesis path of the product, its production path can often be split into multiple production steps, and each production step requires multiple production lines. Taking a pharmaceutical company's production of a drug compound for treating cardiovascular diseases as an example, since the synthesis path of this drug compound will be relatively complex, including multiple production steps, and each production step has multiple production lines. Taking the production of a certain compound divided into four production steps: raw material preparation, synthesis reaction, purification and refinement, and packaging and warehousing as an example for illustration. The raw material preparation step includes 3 production lines, which are responsible for receiving basic chemical raw materials and conducting purity detection, grinding and screening some solid raw materials, and storing and removing impurities from liquid raw materials respectively. The synthesis reaction step includes 2 production lines, which are to conduct the main reaction in the reactor, mix and react the pre-treated raw materials according to a specific formula and process to generate intermediate products, and conduct side reaction treatment on the products after the main reaction to remove impurities and unnecessary by-products respectively. The purification and refinement step includes 2 production lines, which are to preliminarily purify the intermediate products by the crystallization method and further improve the purity of the products by using chromatographic separation technology. The packaging and warehousing step includes 2 production lines, which are to package the final drug compound and conduct labeling, inspection, and warehousing operations on the packaged products respectively.

[0043] Step S2, constructing a corresponding scheduling model based on the production lines, and using the scheduling model to perform pre-solution of the production scheduling for each production line.

[0044] The constructing of the corresponding scheduling model based on the production lines includes the following steps:

[0045] Define constants for consumables, consumption quantity, output products, output quantity, delivery time, and production equipment utilization rate; define time variables, allocation variables, and demand existence variables; define allocation constraints, resource constraints, and reservoir constraints; define production line delivery time, production equipment utilization rate, and production equipment consumption quantity.

[0046] In one example, define the consumable as input[i], the consumption quantity as inputAmount[i], the output product as output[i], the delivery time as deliver[i], the output quantity as outputAmount[i], and the production equipment utilization rate as cost[j].

[0047] For the time variable, start[i] is the start time of production line i, and end[i] is the end time of production line i, which are constants for the arranged production lines.

[0048] For the allocation variable, assign[i,j] = 1 indicates that production line i is allocated to production equipment j, which is a constant for the arranged demand.

[0049] For the demand existence variable, present[i] = 1 indicates that the production line is retained, present[i] = 0 indicates that the current production line will be replaced, and present[i] = 1 for the unarranged production lines.

[0050] For the allocation constraint, each production line is arranged on one production equipment;

[0051] If present[i] = 1, then

[0052] If present[i] = 0, then

[0053] For the resource constraint, the time of two production lines on the same production equipment does not conflict. For example, the time of two production lines i1 and i2 on the same production equipment j does not conflict;

[0054] When assign[i1,j] = assign[i2,j] = 1, start[i1] ≥ end[i2], or end[i1] ≤ start[i2].

[0055] For the reservoir constraint, the output quantity of output products at any time is greater than the consumption quantity. For example, for the output product compound, the output quantity at any time is greater than the consumption quantity;

[0056] For any time t,

[0057]

[0058] Among them, if(present[i]&input[i]&start[i]≤t,-inputAmount[i],0) is expressed as: if present[i]&input[i]&start[i]≤t, the output is -inputAmount[i]; otherwise, the output is 0.

[0059] if(present[i]&output[i]&end[i]≤t,outputAmount[i],0) is expressed as: if present[i]&output[i]&end[i]≤t, the output is outputAmount[i]; otherwise, the output is 0.

[0060] The calculation formula for the production line delivery date is:

[0061]

[0062] Among them, if(present[i]&end[i]<deliver[i],1,0) is expressed as: if present[i]&end[i]<deliver[i], the output is 1; otherwise, the output is 0. present[i] is the existence variable of production line i, end[i] is the end time of production line i, and deliver[i] is the delivery date of production line i.

[0063] The calculation formula for the utilization rate of production equipment is:

[0064]

[0065] Among them, is expressed as: the maximum value of assign(i,j)*end[i] within the range of i from 1 to n. assign(i,j) means production line i is assigned to production equipment j, end[i] is the end time of production line i, and start[i] is the start time of production line i.

[0066] The calculation formula for the consumption of production equipment is:

[0067]

[0068] Among them, assign(i,j) means production line i is assigned to production equipment j, end[i] is the end time of production line i, start[i] is the start time of production line i, and cost[j] is the usage rate of production equipment.

[0069] In one example, batch variables are defined on each production line, as well as the batch production output corresponding to each batch variable; let the total product demand satisfy the following formula:

[0070]

[0071] where tol A represents the total product demand for Product A, n A represents the number of production lines that Product A has, bch A,i represents the number of batches of Product A on the i-th production line, p A,i represents the production output of Product A in a single batch, and int() represents converting the judgment condition into an integer operation.

[0072] The value range of the batch variables on each production line is limited, and the value range is: where k represents 1 ≤ k ≤ n A ; Let the reservoir constraint be ignored in the scheduling model, and on each production line, pre-solution of the production line is performed for each batch variable within the value range.

[0073] For example, for the case where there are multiple batches with high complexity of a compound on a certain production line, due to the large number of batch requirements, the computational complexity increases exponentially. After limiting the batch value range, the computational complexity decreases.

[0074] Taking 3 production lines train as an example, the output of one batch of each production line train is 1 kg. If a total of 100 kg needs to be produced, let the number of batches of each production line train be x1, x2, x3. At this time, it is easy to know that 0 <= x i <= 100. When

[0075] when the batches are not limited, x1 + x2 + x3 = 100, the number of solutions = comb(100 + 3 - 1, 3 - 1) = 5151; when

[0076] when the batches are limited, the value range of x i is limited to {0, 100 / 1, 100 / 2, 100 / 3} = {0, 33, 34, 50, 100} (100 / 3 cannot be divided evenly and needs to be rounded up and down), x1 + x2 + x3 = 10, the number of solutions = 9. It can be seen from the computational complexity that in this example, the complexity is reduced to 9 / 5151 = 0.17%.

[0077] In one example, the reservoir constraint is simplified. For the situation where Product A is consumed during the production of Product B, in order to maintain the feeding balance between Product A and Product B, the reservoir constraint is defined as:

[0078] Among them, product A has n A production lines. The i-th production line has a total of bch A,i batches, and the production output per batch is p A,i , the start time of each batch is start A,i , and the single-batch time is d A,i ; Product B has n B production lines. The i-th production line has a total of bch B,i batches, and the consumption output per batch is p B,i , the start time is start B,i , and the single-batch time is d B,i . It is set that bch A,i , bch B,i , start A,i , start B,i are all variables, and d A,i , d B,i are constants;

[0079] Keep the judgment conditions in the above formula unchanged, and simplify the value range of the constraint time point t to the start time and end time of each production line. That is, for compound A and compound B, traverse the start time and end time of each production line, and perform reservoir constraint checks only at the two time nodes of the start time and end time. That is, the reservoir constraint checks for compound A and compound B are as follows:

[0080] {start A,i , start A,i + bch A,i * d A,i , i = 1…n A}, {start B,i , start B,i + bch B,i * d B,i , i = 1…n B}.

[0081] Through the simplified processing of the reservoir constraint, the solution complexity of the production line scheduling with multiple batches can be reduced, thereby reducing the complexity of the overall production scheduling and improving the efficiency of the production scheduling.

[0082] Step S3, add a destruction operator to the solution scheme of the pre-solution of the production line, perform destruction adjustment on the equipment conflict problem in the solution scheme, and then add a repair operator to perform repair adjustment on the solution scheme after the destruction adjustment. Continuously iterate the destruction adjustment and repair adjustment until the optimal production scheduling results of all production lines that meet the total product demand are determined.

[0083] To solve the problem of equipment conflicts in the pre-solution of the production line, a destruction operator and a repair operator are introduced during the optimization of the scheduling to achieve continuous iterative optimization to determine the optimal production schedule.

[0084] Before the scheduling execution in the pre-solution of the production line, a comprehensive inspection of the equipment usage of all production lines is carried out to identify equipment conflicts. When introducing the destruction operator, a destruction strategy of shuffling the equipment usage conflict time points is adopted to disrupt the original production schedule that may cause conflicts. After the destruction adjustment, the impact on the overall production schedule is evaluated, various possible problems are evaluated, and then according to the evaluation results, a repair operator is introduced for repair, so that the optimized production schedule conforms to the production logic and time requirements again.

[0085] This destruction adjustment and repair adjustment is a continuously repeated process. Each iteration re-detects equipment conflicts. Once new conflicts are found, the destruction operator is used for adjustment again, and then the repair operator is used for repair. After multiple iterations, when all equipment conflicts are effectively resolved and the total product demand is met, the final optimal production schedule result is determined. At this time, the production task arrangements, time allocations, and equipment usages of each production line can reach the best state, and the production of pharmaceutical compounds can be completed efficiently and stably, achieving the maximization of production efficiency and the minimization of costs.

[0086] In an example, an adaptive large neighborhood search algorithm is used to select the operators used iteratively and adaptively.

[0087] Specifically, for the pre-solution plan, the algorithm discovers that there are task conflicts on equipment A and equipment B within the time windows t1 - t2 and t3 - t4. At this time, equipment A and equipment B will be regarded as the candidate areas of the horizontal destruction operator, and the time windows t1 - t2 and t3 - t4 will be regarded as the candidate areas of the vertical destruction operator. According to the performance of the historical operators, adaptively decide whether to select the vertical destruction operator or the horizontal destruction operator in this round of iteration. If the horizontal destruction operator is selected in this round, the algorithm will fix the current scheduling plans of other equipment, relax the scheduling plans on equipment A and B, and use the repair operator to re-solve and optimize the new sub-problem to the optimal state. If the vertical destruction operator is selected, the algorithm will fix the current scheduling plans of other windows, relax the scheduling plans within the t1 - t2 and t3 - t4 windows, and re-optimize based on the repair operator.

[0088] The second embodiment of the present invention discloses a production scheduling system, including a production line splitting module, a pre-solution module, and an optimization module. The production line splitting module is used to split a production project according to the product production path to form multiple production steps, and each production step includes multiple production lines. The pre-solution module is used to construct a corresponding scheduling model based on the production lines, and use the scheduling model to perform pre-solution of the production scheduling for each production line. The optimization module is used to add a destruction operator to the solution obtained from the pre-solution of the production line, perform destruction adjustment on the equipment conflict problem in the solution, then add a repair operator to perform repair adjustment on the solution after the destruction adjustment, and continuously iterate the destruction adjustment and the repair adjustment until the optimal production scheduling results of all production lines that meet the total product demand are determined.

[0089] Since the first embodiment corresponds to this embodiment, this embodiment can be implemented in cooperation with the first embodiment. The relevant technical details mentioned in the first embodiment are still valid in this embodiment, and the technical effects achievable in the first embodiment can also be achieved in this embodiment. To avoid repetition, they will not be elaborated here. Correspondingly, the relevant technical details mentioned in this embodiment can also be applied in the first embodiment.

[0090] The third embodiment of the present invention relates to a production scheduling device, including:

[0091] At least one processor; a memory coupled to the at least one processor, the memory storing executable instructions, wherein the executable instructions, when executed by the at least one processor, cause the method steps of the first aspect of the present invention to be implemented.

[0092] For the production scheduling device provided by the embodiment of the present invention, the processor and the memory can be provided separately or integrated together.

[0093] For example, the memory can include random access memory, flash memory, read-only memory, programmable read-only memory, non-volatile memory, or registers, etc. The processor can be a central processing unit (CPU), etc. Or a graphic processing unit (GPU). The memory can store executable instructions. The processor can execute the executable instructions stored in the memory to implement the various processes described herein.

[0094] It can be understood that the memory in this embodiment can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be ROM (Read-Only Memory), PROM (Programmable ROM), EPROM (Erasable PROM), EEPROM (Electrically EPROM), or flash memory. The volatile memory can be RAM (Random Access Memory), which is used as an external cache. By way of example but not limitation, many forms of RAM are available, such as SRAM (Static RAM), DRAM (Dynamic RAM), SDRAM (Synchronous DRAM), DDR SDRAM (Double Data Rate SDRAM), ESDRAM (Enhanced SDRAM), SLDRAM (Synchlink DRAM), and DRRAM (Direct Rambus RAM). The memory 42 described herein is intended to include but not be limited to these and any other suitable types of memory.

[0095] In some embodiments, the memory stores the following elements, an upgrade package, an executable unit, or a data structure, or a subset thereof, or an extended set thereof: an operating system and an application program.

[0096] Among them, the operating system includes various system programs, such as a framework layer, a core library layer, a driver layer, etc., for implementing various basic services and processing hardware-based tasks. The application program includes various application programs for implementing various application services. The program for implementing the method of the embodiment of the present invention can be included in the application program.

[0097] In the embodiment of the present invention, the processor, by calling the program or instruction stored in the memory, specifically, the program or instruction stored in the application program, is used to execute the method steps provided in the first embodiment.

[0098] The fourth embodiment of the present invention further provides a chip for executing the method in the above first embodiment. Specifically, the chip includes: a processor for calling and running a computer program from the memory, so that a device installed with the chip is used to execute the method in the above first embodiment.

[0099] The fifth embodiment of the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the method according to the first embodiment of the present invention are implemented.

[0100] For example, the machine-readable storage medium may include, but is not limited to, various known and unknown types of non-volatile memories.

[0101] The sixth embodiment of the present invention also provides a computer program product, including computer program instructions, which cause a computer to execute the method in the above-mentioned first embodiment.

[0102] In summary, the production scheduling provided by the present invention splits a production project into multiple production steps, and then splits each production step into multiple production lines. A scheduling model is constructed with the production line as the granularity. By simplifying the reservoir constraint, the complexity of scheduling solution in the production line is reduced. The adaptive large neighborhood search algorithm is introduced to iteratively optimize the pre-solution of the production line, so as to quickly find a feasible solution to the production scheduling problem with high complexity in a single step within a limited time.

[0103] The preferred specific embodiments of the present invention have been described in detail above. It should be understood that those of ordinary skill in the art can make many modifications and variations according to the concept of the present invention without creative labor. Therefore, all technical solutions that can be obtained by those skilled in the art in the technical field of the present invention based on the concept of the present invention through logical analysis, reasoning or limited experiments on the basis of the prior art should be within the protection scope determined by the claims.

Claims

1. A production scheduling method, characterized in that: The following steps are involved: Split the production project according to the product production path to form multiple production steps, each of which includes multiple production lines; Build a corresponding scheduling model based on the production line, and use the scheduling model to pre-solve the production schedule of each production line; A destruction operator is added based on the pre-solved solution of the production line to make a destruction adjustment to the equipment conflict problem in the solution. Then a repair operator is added to make a repair adjustment to the solution after the destruction adjustment. The destruction adjustment and repair adjustment are continuously iterated until the optimal production scheduling result for all production lines that meet the total product demand is determined.

2. The production scheduling method according to claim 1, characterized in that: The construction of a corresponding scheduling model based on the production line includes the following steps: Define constants for consumables, consumption, outputs, output, lead times, and production equipment utilization; Define time variables, allocation variables, and demand existence variables; Define allocation constraints, resource constraints, and reservoir constraints; Define production line lead time, production equipment utilization and production equipment consumption.

3. The production scheduling method according to claim 2, characterized in that: Defining batch variables on each production line and the batch production output corresponding to each batch variable; Let the total product demand satisfy the following formula: Among them, tol A represents the total product demand of product A, n A Indicates the number of production lines for product A, bch A,i represents the number of batches of product A on the i-th production line, p A,i It represents the production output of product A in a single batch, and int() means converting the judgment condition into an integer operation.

4. The production scheduling method according to claim 3, characterized in that: The value range of the batch variables on each production line is limited to: Where k represents, 1≤k≤n A ; The reservoir constraint is ignored in the scheduling model, and the production line pre-solution is performed on each production line for each batch variable within the value range.

5. The production scheduling method according to claim 2, characterized in that: In order to maintain the supply balance between product A and product B, the water reservoir constraint is defined as: Where product A has n A Production lines, the i-th production line has a total of bch A,i batches, each batch produces p A,i , each batch starts at start time A,i , single batch time d A,i ; Product B has n B Production lines, the i-th production line has a total of bch B,i batches, each batch consumes output p B,i , start time start B,i , single batch time d B,i , set bch A,i ,bch B,i ,start A,i ,start B,i All variables, d A,i ,d B,i is a constant; Keeping the judgment condition in the above formula unchanged, the value range of the constraint time point t is simplified to the start time and end time of each production line.

6. The production scheduling method according to claim 1, characterized in that: The destruction operator includes a vertical destruction operator and a horizontal destruction operator. The vertical destruction operator is based on a time window and divides the scheduling cycle in the production line pre-solution into multiple vertical fields according to a preset time granularity for destruction adjustment. The horizontal destruction operator divides the scheduling plan in the production line pre-solution into different horizontal fields based on the production line for destruction adjustment.

7. The production scheduling method according to claim 6, characterized in that: In the adjustment process of the destruction operator and the repair operator, an adaptive large neighborhood search algorithm is used to select each operator for iterative use.

8. A production scheduling system, characterized in that: include: The production line splitting module is used to split the production items according to the product production path to form multiple production steps, each of which includes multiple production lines; The pre-solving module is used to build a corresponding scheduling model based on the production line, and use the scheduling model to pre-solve the production schedule of each production line; The optimization module is used to add a destruction operator to the pre-solved solution of the production line, perform destruction adjustments on the equipment conflict problems in the solution, and then add a repair operator to repair the solution after the destruction adjustment. The destruction adjustment and repair adjustment are continuously iterated until the optimal production scheduling results for all production lines that meet the total product demand are determined.

9. A production scheduling device, comprising at least one processor; a memory coupled to the at least one processor, the memory storing executable instructions, characterized in that: The executable instructions, when executed by the at least one processor, enable the steps of the method according to any one of claims 1 to 7 to be implemented.

10. A chip, characterized in that: It comprises a processor, which is used to call and run a computer program from a memory, so that a device equipped with the chip executes the steps of the method as claimed in any one of claims 1 to 7.

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