Flow shop scheduling method, device and electronic equipment

Abstract

The application provides a kind of flow shop scheduling method, device and electronic equipment, it is related to workshop scheduling technical field.The method comprises: based on heuristic algorithm, the initial arrangement sequence and initial maximum completion time of all to be processed workpieces are obtained;Target combination sequence obtained from initial arrangement sequence is sequentially inserted into all possible new positions of the arrangement sequence after removing target combination sequence in initial arrangement sequence and the maximum completion time of each obtained temporary arrangement sequence is calculated, until all target combination sequences are traversed, target combination sequence includes at least one target combination sub-sequence determined by at least two adjacent sequences;The minimum maximum completion time of the maximum completion time of all temporary arrangement sequences and initial maximum completion time is obtained, and the arrangement sequence corresponding to the minimum maximum completion time is determined as the production scheduling scheme of to be processed workpieces.The technical scheme of the embodiment of the application can realize the optimization of maximum completion time, and improve production efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of workshop scheduling, and in particular to a flow workshop scheduling method, device and electronic equipment. Background Art

[0002] Shop scheduling is a key link in the shop production process. Research on the flow shop scheduling problem (FSP), especially the no-wait flow shop scheduling problem (NWFSSP), can help enterprises improve production efficiency and resource utilization, and enhance production reliability.

[0003] In NWFSSP, a workpiece consists of multiple processes, each of which is processed on a single piece of equipment. All workpieces are processed in the same order on each piece of equipment. Furthermore, a workpiece can only be processed on one piece of equipment at a time, and each piece of equipment can only process one workpiece at a time. Furthermore, NWFSSP requires that the processing of the same workpiece be completed continuously. While meeting these requirements, arranging the production processes of the workpieces to minimize cycle time is a key issue facing the field of shop floor scheduling. Summary of the Invention

[0004] In view of the above problems existing in the prior art, the present invention provides a flow shop scheduling method, device and electronic equipment to optimize the maximum completion time of workpieces to be processed in the flow shop.

[0005] The present invention provides a flow shop scheduling method, comprising:

[0006] Obtain the initial arrangement sequence and initial maximum completion time of all workpieces to be processed based on a heuristic algorithm;

[0007] Acquire a target combination sequence from the initial permutation sequence, wherein the target combination sequence includes at least one target combination subsequence, and the target combination subsequence is at least two adjacent sequences in the initial permutation sequence;

[0008] Inserting the target combination sequence into all possible new positions in the remaining sequence in sequence, and calculating the maximum completion time of each temporary permutation sequence obtained, until all target combination sequences are traversed, and the remaining sequence is the permutation sequence after removing the target combination sequence from the initial permutation sequence;

[0009] The minimum maximum completion time among the maximum completion times of all temporary arrangement sequences and the initial maximum completion times is obtained, and the arrangement sequence corresponding to the minimum maximum completion time is determined as the production scheduling plan for the workpiece to be processed.

[0010] According to a flow shop scheduling method provided by the present invention, obtaining a target combination sequence from the initial arrangement sequence includes:

[0011] At least two adjacent sequences are selected from the initial arrangement sequence and combined to obtain the target combination sequence.

[0012] According to a flow shop scheduling method provided by the present invention, obtaining a target combination sequence from the initial arrangement sequence includes:

[0013] Selecting at least two adjacent sequences from the initial arrangement sequence and combining them to obtain a first combination sequence;

[0014] Selecting at least two adjacent sequences from the permutation sequence after removing the first combination sequence from the initial permutation sequence and combining them to obtain a second combination sequence;

[0015] The first combination sequence and the second combination sequence are permuted and combined, and the target combination sequence is determined based on the permutation and combination result.

[0016] According to a flow shop scheduling method provided by the present invention, determining the target combination sequence based on the permutation and combination results includes:

[0017] Determining at least one of the permutation and combination results as the target combination sequence;

[0018] Alternatively, at least one of the permutation and combination results and the first combination sequence are respectively determined as the target combination sequence.

[0019] According to a flow shop scheduling method provided by the present invention, the heuristic algorithm-based method for obtaining the initial arrangement sequence and initial maximum completion time of all workpieces to be processed includes:

[0020] Obtain an initial job list, wherein the initial job list includes the total processing time of each workpiece to be processed on all processing equipment;

[0021] A heuristic algorithm is used to solve the initial solution of the initial job list to obtain the initial arrangement sequence and initial maximum completion time of all workpieces to be processed.

[0022] According to a flow shop scheduling method provided by the present invention, the heuristic algorithm is the NEH algorithm.

[0023] The present invention also provides a flow shop scheduling device, comprising:

[0024] A first acquisition module is used to acquire an initial arrangement sequence and an initial maximum completion time of all workpieces to be processed based on a heuristic algorithm;

[0025] A second acquisition module is configured to acquire a target combination sequence from the initial permutation sequence, wherein the target combination sequence includes at least one target combination subsequence, and the target combination subsequence is at least two adjacent sequences in the initial permutation sequence;

[0026] a calculation module, configured to sequentially insert the target combination sequence into all possible new positions in the remaining sequence and calculate the maximum completion time of each temporary permutation sequence obtained until all target combination sequences are traversed, wherein the remaining sequence is the permutation sequence after removing the target combination sequence from the initial permutation sequence;

[0027] The determination module is used to obtain the maximum completion time of all temporary arrangement sequences and the minimum maximum completion time among the initial maximum completion times, and determine the arrangement sequence corresponding to the minimum maximum completion time as the production scheduling plan for the workpiece to be processed.

[0028] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the flow shop scheduling method described above is implemented.

[0029] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the above-described flow shop scheduling methods.

[0030] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements any of the above-mentioned flow shop scheduling methods.

[0031] The flow shop scheduling method, device, and electronic device provided by the present invention obtain a target combination sequence from an initial permutation sequence of all workpieces to be processed obtained based on a heuristic algorithm. The target combination sequence includes at least one target combination subsequence, which is at least two adjacent sequences in the initial permutation sequence. The target combination sequence is then sequentially inserted into all possible new positions in the permutation sequence after the target combination sequence is removed from the initial permutation sequence, and the maximum completion time of each temporary permutation sequence obtained is calculated until all target combination sequences are traversed, thereby calculating multiple permutations and combinations of the initial permutation sequence and the maximum completion time. The minimum maximum completion time among the maximum completion times of all temporary permutation sequences and the initial maximum completion times is then obtained, and the permutation sequence corresponding to the minimum maximum completion time is determined as the production scheduling sequence for the workpieces to be processed. The production scheduling sequence solved by the heuristic algorithm can be further permuted and combined to obtain multiple possible production scheduling sequences. The minimum maximum completion time is determined from the maximum completion times of all possible production scheduling sequences and the initial permutation sequence. The obtained maximum completion time is more optimal, thereby optimizing the maximum completion time of the workpieces to be processed in the flow shop and improving production efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions in the present invention or the prior art, a brief introduction is given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0033] Figure 1 This is a schematic diagram of the working principle of the displacement flow workshop provided by the present invention;

[0034] Figure 2 This is a schematic diagram of the working principle of the no-waiting flow workshop provided by the present invention;

[0035] Figure 3 This is one of the flow charts of the flow shop scheduling method provided by the present invention;

[0036] Figure 4 This is one of the principle diagrams of the method for obtaining a target combination sequence from an initial arrangement sequence provided by the present invention;

[0037] Figure 5 This is the second schematic diagram of the principle of the method for obtaining a target combination sequence from an initial arrangement sequence provided by the present invention;

[0038] Figure 6 This is the second flow chart of the flow shop scheduling method provided by the present invention;

[0039] Figure 7 1 is a schematic diagram of the principle of performing a first optimization arrangement on an initial arrangement sequence using a first optimization strategy provided by the present invention;

[0040] Figure 8 Schematic diagram of the principle of performing a second optimization arrangement on the initial arrangement sequence using the second optimization strategy provided by the present invention;

[0041] Figure 9 Schematic diagram of the principle of performing a third optimization arrangement on the initial arrangement sequence using the third optimization strategy provided by the present invention;

[0042] Figure 10 It is a structural schematic diagram of the flow shop scheduling device provided by the present invention;

[0043] Figure 11 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0044] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0045] The flow shop scheduling problem (FSP) has long been a key research issue in enterprise production and a crucial component of smart factory scheduling. FSP is a strongly nondeterministic polynomial (NP-hard) problem that is typically difficult to solve. Therefore, research on assembly line scheduling algorithms is crucial for reducing runtime, improving production efficiency, and balancing computational time and solution quality.

[0046] In FSP, the permutation flow shop problem (PFSP) is a special type of optimization scheduling problem, which is defined as: given a limited number of processing equipment and workpieces to be processed, and all processing equipment complete each workpiece in the same order, find the best work order to maximize the performance index, where the performance index can include at least one of the total delay, manufacturing time, total process time, production cost and energy consumption. For example, Figure 1 The schematic diagram of the working principle of the replacement flow workshop is shown as an example. Figure 1 As shown, taking the example of four workpieces to be processed, workpiece 1 to workpiece 4, which are processed in processing equipment M1 to M3, each workpiece to be processed is processed in the same order through processing equipment M1 to M3, and each workpiece to be processed has its corresponding processing time in each processing equipment.

[0047] When all processes in a permutation flow shop must be completed without interruption, it is called the No-Wait Flow Shop Scheduling Problem (NWFSSP), for example, in the steel industry, molten iron cannot wait. Based on this, NWFSSP can be described as: given m processing equipment and n workpieces to be processed, the processing order of all workpieces to be processed on each processing equipment is the same; at the same time, it is agreed that one processing equipment can only process one workpiece to be processed at the same time, and one workpiece to be processed can only be processed on one processing equipment at the same time; moreover, the processing of the same workpiece to be processed must be completed continuously, that is, there is no waiting time for adjacent processes of the same workpiece to be processed, which is determined by the processing time of each process. Based on this, the problem to be solved is how to arrange the production processes to obtain the minimum production cycle while meeting the above requirements. For example, Figure 2 The schematic diagram of the working principle of the no-waiting flow shop is shown as an example. Figure 2 As shown, taking the example of four workpieces to be processed, namely workpiece 1 to workpiece 4, being processed in processing equipment M1 to M3, each workpiece to be processed has its corresponding processing time in each processing equipment, and each workpiece to be processed is processed in the same order through processing equipment M1 to M3, and the processing on each processing equipment is completed continuously.

[0048] In related technologies, heuristic algorithms can be used to deal with flow shop scheduling problems. For example, heuristic algorithms such as the Nawaz-Enscore-Ham (NEH) algorithm, the Palmer algorithm, or the Rapid Access (RA) algorithm can be used to deal with flow shop scheduling problems. Heuristic algorithms use problem-specific knowledge and experience to generate solutions, which can obtain suboptimal solutions in a shorter period of time and ensure the local optimality of the processing sequence to a certain extent, but they may not necessarily provide the shortest or optimal processing sequence. Further improvements to the heuristic algorithm are very important for maintaining the constructive characteristics of the initial algorithm to obtain clear and repeatable results. Solving the NWFSSP by further optimizing the solution generated by the heuristic algorithm will help optimize the maximum completion time and improve production efficiency.

[0049] Based on this, in an embodiment of the present invention, the production scheduling sequence solved by the heuristic algorithm can be further optimized by permutation and combination, and the sequence with the minimum maximum completion time can be determined from all permutation and combination sequences and the production scheduling sequence solved by the heuristic algorithm as the production scheduling solution for the workpiece to be processed. Based on the production scheduling sequence solved by the heuristic algorithm, at least two adjacent sequences can be combined to obtain a target combination subsequence, and at least one target combination subsequence can be combined into a target combination sequence. The target combination sequence is then combined and permuted with the remaining sequences, and the maximum completion time of each temporary permutation sequence obtained is calculated until all target combination sequences are traversed. The sequence with the minimum maximum completion time can be determined from all temporary permutation sequences and the production scheduling sequence solved by the heuristic algorithm with the minimum maximum completion time as the final production scheduling solution.

[0050] The following combination Figure 3-Figure 9 The present invention describes a flow shop scheduling method. This method can be applied to electronic devices such as servers, mobile phones, and computers, or flow shop scheduling systems. It can also be applied to a flow shop scheduling device installed in such electronic devices. The flow shop scheduling device can be implemented using software, hardware, or a combination of both.

[0051] Figure 3 One of the flow charts of the flow shop scheduling method provided by the embodiment of the present invention is exemplified. Figure 3 As shown, the flow shop scheduling method may include the following steps 310 to 340.

[0052] Step 310: Obtain the initial arrangement sequence and initial maximum completion time of all workpieces to be processed based on a heuristic algorithm.

[0053] Given m processing equipment and n workpieces to be processed, the minimum maximum completion time and the processing sequence corresponding to the maximum completion time for processing these n workpieces to be processed on these m processing equipment can be solved based on a heuristic algorithm, and the initial maximum completion time and initial arrangement sequence for processing these n workpieces to be processed on these m processing equipment can be obtained.

[0054] In an example embodiment, obtaining the initial arrangement sequence and initial maximum completion time of all workpieces to be processed based on a heuristic algorithm may include: obtaining an initial job list, where the initial job list includes the total processing time of each workpiece to be processed on all processing equipment; and using a heuristic algorithm to solve the initial solution of the initial job list to obtain the initial arrangement sequence and initial maximum completion time of all workpieces to be processed.

[0055] Exemplarily, the heuristic algorithm may be, for example, the NEH algorithm.

[0056] Step 320: Obtain a target combination sequence from the initial permutation sequence, where the target combination sequence includes at least one target combination subsequence, and the target combination subsequence is at least two adjacent sequences in the initial permutation sequence.

[0057] After obtaining the initial arrangement sequence and initial maximum completion time of all workpieces to be processed based on the heuristic algorithm, at least two adjacent sequences in the initial arrangement sequence can be combined to obtain a target combination subsequence, and one or more different target combination subsequences can be obtained and combined to obtain a target combination sequence.

[0058] In an exemplary embodiment, any target combination subsequence can be used as the target combination sequence. Accordingly, obtaining the target combination sequence from the initial permutation sequence may include: selecting at least two adjacent sequences from the initial permutation sequence and combining them to obtain the target combination sequence. It is understandable that multiple different target combination sequences can be obtained from the initial permutation sequence. For example, Figure 4 One of the schematic diagrams of the principle of the method for obtaining the target combination sequence from the initial arrangement sequence provided by the present invention is exemplified, referring to Figure 4 As shown, taking the initial arrangement sequence including 4 sequences as an example, numbered from 1 to 4 in sequence, it can be determined as follows Figure 4 The five target combination subsequences shown can be used as target combination sequences, and then permuted and combined with their corresponding remaining sequences to calculate the maximum completion time for each permutation and combination sequence. For example, the first target subsequence can be inserted between numbers 3 and 4 and after number 4 to obtain two permutations and combinations corresponding to the first target subsequence. The remaining sequence is the permutation sequence after removing the target combination sequence from the initial permutation sequence.

[0059] In an example embodiment, at least two groups of target combination subsequences may be combined to form a target combination sequence. For example, at least two adjacent groups of target combination subsequences may be combined. Accordingly, obtaining the target combination sequence from the initial permutation sequence may include: selecting at least two adjacent sequences from the initial permutation sequence and combining them to obtain a first combination sequence; selecting at least two adjacent sequences from a permutation sequence after removing the first combination sequence from the initial permutation sequence and combining them to obtain a second combination sequence; and permuting and combining the first combination sequence and the second combination sequence, and determining the target combination sequence based on the permutation and combination results.

[0060] Exemplarily, determining the target combination sequence based on the permutation and combination results may include: determining at least one of the permutation and combination results as the target combination sequence; or determining at least one of the permutation and combination results and the first combination sequence as the target combination sequence. Figure 5The second schematic diagram of the principle of the method for obtaining the target combination sequence from the initial arrangement sequence provided by the present invention is shown as an example. Figure 5 As shown, there are 10 sequences in the initial permutation sequence, which are numbered 1 to 10 in order. For example, the sequences numbered 2 and 3 can be combined to obtain the first combination sequence. Then, the sequences numbered 7 to 9 are selected from the remaining sequences after removing 2 and 3 to obtain the second combination sequence. Then, the first combination sequence can be placed before the second combination sequence and combined to obtain the following: Figure 5 The target combination sequence "2-3-7-8-9" shown in the figure can be subsequently permuted and combined with the remaining sequences, and the maximum completion time of each permutation and combination sequence can be calculated until all target combination sequences obtained in this combination method are traversed; further, the first combination sequence can be placed after the second combination sequence to expand more target combination sequences. Alternatively, Figure 5 The corresponding permutations and combinations are Figure 4 The corresponding permutation and combination methods are merged, and the combination sequences obtained by the two permutation and combination methods are respectively used as the target combination sequences.

[0061] Step 330: insert the target combination sequence into all possible new positions in the remaining sequence in sequence, and calculate the maximum completion time of each temporary permutation sequence obtained, until all target combination sequences are traversed and the remaining sequence is the permutation sequence after removing the target combination sequence from the initial permutation sequence.

[0062] Whether using Figure 4 The corresponding permutation and combination methods are used to obtain multiple target combination sequences. Figure 5 The corresponding permutation and combination methods obtain multiple target combination sequences, or Figure 4 The corresponding permutations and combinations are Figure 5 Multiple target combination sequences are obtained by merging the corresponding permutation and combination methods. For each target combination sequence, the target combination sequence can be inserted into all possible new positions in the permutation sequence after removing the target combination sequence from the initial permutation sequence, and the maximum completion time of each temporary permutation sequence is calculated until all target combination sequences are traversed.

[0063] Step 340: Obtain the minimum maximum completion time among the maximum completion times of all temporary arrangement sequences and the initial maximum completion times, and determine the arrangement sequence corresponding to the minimum maximum completion time as the production scheduling plan for the workpiece to be processed.

[0064] For each target combination sequence, a plurality of temporary permutation sequences corresponding to the target combination sequence can be obtained by performing permutation combination on the permutation sequence obtained by removing the target combination sequence from the initial permutation sequence. In an example embodiment, the minimum time can be determined from the maximum completion times of the plurality of temporary permutation sequences corresponding to each target combination sequence to obtain the minimum maximum completion time corresponding to each target combination sequence, and then the minimum maximum completion time required finally can be obtained by taking the minimum time from the initial maximum completion time and the minimum maximum completion times corresponding to all target combination sequences. In an example embodiment, the maximum completion times of all temporary permutation sequences of all target combination sequences can be calculated first, and then the minimum maximum completion time required finally can be obtained by determining the minimum time from these maximum completion times and the initial maximum completion time. In an example embodiment, a variable can be set to save the minimum maximum completion time, the variable is initialized to save the initial maximum completion time, and then the maximum completion time of each obtained temporary permutation sequence is compared with the current value of the variable, so that the minimum value obtained by comparison is saved in the variable at all times until all permutation combination sequences are traversed, and the final value of the variable is the minimum maximum completion time required.

[0065] After obtaining the minimum maximum completion time, the permutation sequence corresponding to the minimum maximum completion time can be determined as the production scheduling scheme of the workpieces to be processed, and the processing of the workpieces to be processed can be completed in the minimum production cycle based on the production scheduling scheme, thereby improving the production efficiency and reducing the production cost.

[0066] The flow shop scheduling method, device and electronic equipment provided by the present application obtain target combination sequences from the initial permutation sequence of all workpieces to be processed based on the heuristic algorithm, the target combination sequence includes at least one target combination sub-sequence, the target combination sub-sequence is at least two adjacent sequences in the initial permutation sequence, the target combination sequence is sequentially inserted into all possible new positions of the permutation sequence obtained by removing the target combination sequence from the initial permutation sequence, and the maximum completion time of each obtained temporary permutation sequence is calculated until all target combination sequences are traversed, thereby realizing the calculation of the maximum completion time and the permutation combination of the initial permutation sequence. Then, the minimum maximum completion time is obtained from the maximum completion times of all temporary permutation sequences and the initial maximum completion time, and the permutation sequence corresponding to the minimum maximum completion time is determined as the production scheduling sequence of the workpieces to be processed. The production scheduling sequence solved by the heuristic algorithm can be further permuted and combined to obtain a plurality of possible production scheduling sequences, the minimum maximum completion time is determined from these all possible production scheduling sequences and the maximum completion time of the initial permutation sequence, the obtained maximum completion time is more optimal, thereby realizing the optimization of the maximum completion time of the workpieces to be processed in the flow shop, and improving the production efficiency.

[0067] based on Figure 3 The flow shop scheduling method of the corresponding embodiment is further illustrated below by taking the NEH algorithm as an example of a heuristic algorithm to illustrate the flow shop scheduling method provided by the present invention. Figure 6 The second flow chart of the flow shop scheduling method provided by the embodiment of the present invention is exemplified. The flow shop scheduling method can obtain a better maximum completion time by further optimizing the production scheduling solution solved by the NEH algorithm. Figure 6 As shown, the flow shop scheduling method may include the following steps 601 to 612.

[0068] Step 601: Obtain an initial job list.

[0069] The initial job list contains the total processing time for each workpiece across all processing devices. This initial job list can be created by the user. For example, if n workpieces need to be processed on m processing devices, an initial job list of length n can be created, which stores the total processing time for each workpiece on m processing devices.

[0070] Step 602: NEH algorithm is used to solve the initial solution of the initial job list to obtain the initial arrangement sequence of all workpieces to be processed and the initial maximum completion time Makespan.

[0071] After obtaining the initial job list, the NEH algorithm can be used to permutate and combine the total processing time of each workpiece to be processed on m processing equipment saved in the initial job list, and obtain the minimum time among the maximum completion times of these permutation and combination sequences to obtain the initial maximum completion time Makespan, and determine the permutation and combination sequence corresponding to the minimum time as the initial permutation sequence.

[0072] Step 603: Perform a first optimization arrangement on the initial arrangement sequence using a first optimization strategy, and determine the maximum completion time Makespan1 of the first optimization arrangement.

[0073] After obtaining the initial permutation sequence, the first optimization strategy can be used to perform a first optimization permutation on the initial permutation sequence, and the maximum completion time Makespan1 of the first optimization permutation can be determined. Specifically, at least two adjacent sequences in the initial permutation sequence can be combined to obtain multiple target combination sequences. Starting from the first target combination sequence, the target combination sequence is inserted into the new position of the permutation sequence after removing the target combination sequence in the initial permutation sequence. After each insertion, the completion time of the temporary permutation sequence is calculated, and the completion time is compared with the completion time obtained last time and the minimum value is saved until all target combination sequences are traversed. The last saved completion time is the maximum completion time Makespan1 obtained after the first optimization permutation.

[0074] For example, Figure 7 The schematic diagram of the principle of performing the first optimization arrangement of the initial arrangement sequence using the first optimization strategy provided by the embodiment of the present invention is exemplarily shown, referring to Figure 7 As shown in , the initial permutation sequence includes 8 sequences, numbered 1 to 8 in order. At least two adjacent sequences can be used as target combination sequences to obtain all possible target combination sequences. For each target combination sequence, it can be inserted into the new position before and after the remaining sequences and rearranged to obtain multiple temporary permutation sequences. For example, in Figure 7 In the example, the sequences numbered 3 and 4 can be combined and inserted between the sequences numbered 5 and 6 to obtain a temporary permutation sequence. It is understood that the sequences numbered 3 and 4 can be inserted before and after 1, between 5 and 6, between 6 and 7, between 7 and 8, and after 8, traversing all new positions that can be inserted to obtain multiple temporary permutation sequences. It is understood that for Figure 7 The initial permutation sequence can be combined into target combination sequence by combining 2, 3 or even 7 adjacent sequences, and traversing all possible adjacent sequence combinations.

[0075] Step 604: Determine whether Makespan1 is less than Makespan. If so, proceed to step 605; otherwise, proceed to step 606. This allows further optimization of the maximum makespan calculated by the NEH algorithm, shortening the maximum makespan and improving production efficiency.

[0076] Step 605: Assign the value of Makespan1 to Makespan, and then proceed to step 606.

[0077] Step 606: Perform a second optimization arrangement on the initial arrangement sequence using a second optimization strategy, and determine the maximum completion time Makespan2 of the second optimization arrangement.

[0078] After obtaining the initial permutation sequence, a second optimization strategy can be used to perform a second optimization permutation on the initial permutation sequence, and the maximum completion time Makespan2 of the second optimization permutation can be determined. Specifically, the target combination subsequence can be determined from the initial permutation sequence by selecting adjacent sequences in step 603, i.e., at least two adjacent sequences in the initial permutation sequence are determined as the target combination subsequences. Based on this, a target combination subsequence can be first determined, and then a second target combination subsequence is determined from the remaining sequences. These two target combination subsequences are then combined together as a target combination sequence, thereby determining multiple target combination sequences. Starting from the first target combination sequence, the target combination sequence is inserted into the new position of the permutation sequence after removing the target combination sequence in the initial permutation sequence. After each insertion, the completion time of the temporary permutation sequence obtained is calculated, and the completion time is compared with the completion time obtained last time and the minimum value thereof is saved until all target combination sequences are traversed. The final saved completion time is the maximum completion time Makespan2 obtained after the second optimization permutation.

[0079] For example, Figure 8 The schematic diagram of the principle of performing the second optimization arrangement of the initial arrangement sequence using the second optimization strategy provided by the embodiment of the present invention is exemplified. Figure 8 As shown, the initial permutation sequence includes 10 sequences, which are numbered 1 to 10 in order. Two adjacent sequences numbered 2 and 3 can be selected from the sequence to form a first target combination subsequence. Three adjacent sequences numbered 7, 8, and 9 can be selected from the remaining sequence to form a second target combination subsequence. These two target combination subsequences can be combined together to obtain a target combination sequence, which is then inserted into all possible new positions in the remaining sequence, such as Figure 8 can be inserted between numbers 5 and 6 to obtain Figure 8 The temporary permutation sequence shown can be inserted into different new positions to obtain multiple temporary permutation sequences corresponding to the target combination sequence. In this way, multiple target combination sequences and their corresponding temporary permutation sequences can be obtained.

[0080] Step 607: Determine whether Makespan2 is less than Makespan. If so, proceed to step 608; otherwise, proceed to step 609. This allows further optimization of the maximum completion time obtained after the first optimization permutation, further shortening the maximum completion time and improving production efficiency.

[0081] Step 608: Assign the value of Makespan2 to Makespan, and then proceed to step 609.

[0082] Step 609: Perform a third optimization arrangement on the initial arrangement sequence using the third optimization strategy, and determine the maximum completion time Makespan3 of the third optimization arrangement.

[0083] After performing a second optimization permutation on the initial permutation sequence according to the second optimization strategy and determining the maximum completion time of the second optimization permutation, a third optimization strategy may be used to perform a third optimization permutation on the initial permutation sequence and determine the maximum completion time Makespan3 of the third optimization permutation. Specifically, the order of the two target combination subsequences in the target combination sequence determined in step 606 may be reversed to form a new target combination sequence, which is then inserted into all possible new positions in the remaining sequence. After each insertion, the completion time of the temporary permutation sequence is calculated, and the completion time is compared with the last completion time obtained, and the minimum value is saved until all target combination sequences are traversed. The final saved completion time is the maximum completion time Makespan3 obtained after the third optimization permutation.

[0084] For example, based on Figure 8 The permutation and combination of Figure 9 The schematic diagram of the principle of performing the third optimization arrangement on the initial arrangement sequence by using the third optimization strategy provided by the embodiment of the present invention is exemplified. Figure 9 As shown, it is possible to Figure 8 The order of the first target combination subsequence "2-3" and the second target combination subsequence "7-8-9" in the sequence is reversed, and the new target combination sequences are inserted into all possible new positions in the remaining sequence, such as Figure 9 In the example, we can insert it between the sequences numbered 5 and 6 to get Figure 9 Another temporary permutation sequence shown can be inserted into different new positions to obtain multiple temporary permutation sequences corresponding to the target combination sequence. In this way, multiple target combination sequences and their corresponding temporary permutation sequences can be further obtained.

[0085] It is understandable that based on Figure 8 and Figure 9 The calculation method can convert the optimization problem of maximum completion time into an asymmetric traveling salesman problem for calculation, which is conducive to the determination of the minimum production cycle.

[0086] Step 610: Determine whether Makespan3 is less than Makespan. If so, proceed to step 611; otherwise, proceed to step 612. This allows further optimization of the maximum completion time obtained after the second optimization permutation, further shortening the maximum completion time and improving production efficiency.

[0087] Step 611: Assign the value of Makespan3 to Makespan, and then proceed to step 612.

[0088] Step 612: Save the current Makespan and the permutation sequence corresponding to the Makespan.

[0089] After multiple optimization processes, the final Makespan value is the determined minimum maximum completion time. Processing the workpiece according to the arrangement sequence corresponding to the Makespan can shorten the production cycle, improve production efficiency, and save production costs.

[0090] The flow shop scheduling method provided in this example embodiment performs a first optimization arrangement, a second optimization arrangement, and a third optimization arrangement on the initial arrangement sequence solved by the NEH algorithm, and continuously optimizes and schedules the maximum completion time solved by the NEH algorithm based on each optimization arrangement, so as to obtain a better maximum completion time. Processing the workpieces to be processed using the arrangement sequence corresponding to the maximum completion time can effectively shorten the production cycle, obtain the minimum production cycle, improve production efficiency, and reduce production costs.

[0091] The flow shop scheduling device provided by the present invention is described below. The flow shop scheduling device described below and the flow shop scheduling method described above can be referenced to each other.

[0092] Figure 10 The schematic diagram of the structure of the flow shop scheduling device provided by the embodiment of the present invention is shown as an example. Figure 10 As shown, the flow shop scheduling device 1000 may include a first acquisition module 1010, a second acquisition module 1020, a calculation module 1030, and a determination module 1040. The first acquisition module 1010 may be used to acquire the initial permutation sequence and initial maximum completion time of all workpieces to be processed based on a heuristic algorithm; the second acquisition module 1020 may be used to acquire a target combination sequence from the initial permutation sequence, wherein the target combination sequence includes at least one target combination subsequence, and the target combination subsequence is at least two adjacent sequences in the initial permutation sequence; the calculation module 1030 may be used to sequentially insert the target combination sequence into all possible new positions in the remaining sequence and calculate the maximum completion time of each temporary permutation sequence obtained, until all target combination sequences are traversed and the remaining sequence is the permutation sequence after removing the target combination sequence from the initial permutation sequence; the determination module 1040 may be used to acquire the minimum maximum completion time among the maximum completion times of all temporary permutation sequences and the initial maximum completion times, and determine the permutation sequence corresponding to the minimum maximum completion time as the production scheduling solution for the workpieces to be processed.

[0093] In an exemplary embodiment, the second acquisition module 1020 may be specifically configured to select at least two adjacent sequences from the initial arrangement sequence and combine them to obtain a target combination sequence.

[0094] In an example embodiment, the second acquisition module 1020 may include a first selection unit, a second selection unit, and a determination unit. The first selection unit may be configured to select at least two adjacent sequences from an initial permutation sequence and combine them to obtain a first combination sequence; the second selection unit may be configured to select at least two adjacent sequences from a permutation sequence after removing the first combination sequence from the initial permutation sequence and combine them to obtain a second combination sequence; and the determination unit may be configured to permutate and combine the first combination sequence and the second combination sequence, and determine a target combination sequence based on the permutation and combination results.

[0095] In an exemplary embodiment, the determining unit may be specifically configured to determine at least one of the permutation and combination results as the target combination sequence, or to determine at least one of the permutation and combination results and the first combination sequence as the target combination sequences respectively.

[0096] In one exemplary embodiment, the first acquisition module 1010 may include an acquisition unit and a solution unit. The acquisition unit may be configured to acquire an initial job list, which includes the total processing time of each workpiece to be processed on all processing equipment; and the solution unit may be configured to employ a heuristic algorithm to find an initial solution to the initial job list, thereby obtaining an initial arrangement sequence and an initial maximum completion time for all workpieces to be processed.

[0097] In an exemplary embodiment, the heuristic algorithm is the NEH algorithm.

[0098] Figure 11 An example of a physical structure diagram of an electronic device is shown below. Figure 11As shown, the electronic device 1100 may include: a processor 1110 , a communication interface 1120 , a memory 1130 and a communication bus 1140 , wherein the processor 1110 , the communication interface 1120 and the memory 1130 communicate with each other via the communication bus 1140 . The processor 1110 can call the logic instructions in the memory 1130 to execute the steps of the flow shop scheduling method provided by the above-mentioned method embodiments. The flow shop scheduling method may include: obtaining the initial arrangement sequence and initial maximum completion time of all workpieces to be processed based on a heuristic algorithm; obtaining a target combination sequence from the initial arrangement sequence, wherein the target combination sequence includes at least one target combination subsequence, and the target combination subsequence is at least two adjacent sequences in the initial arrangement sequence; inserting the target combination sequence into all possible new positions in the remaining sequence in sequence, and calculating the maximum completion time of each temporary arrangement sequence obtained until all target combination sequences are traversed and the remaining sequence is the arrangement sequence after removing the target combination sequence from the initial arrangement sequence; obtaining the maximum completion time of all temporary arrangement sequences and the minimum maximum completion time among the initial maximum completion times, and determining the arrangement sequence corresponding to the minimum maximum completion time as the production scheduling plan for the workpieces to be processed.

[0099] In addition, the logic instructions in the above-mentioned memory 1130 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0100] On the other hand, the present invention also provides a computer program product, which includes a computer program, which can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the steps of the flow shop scheduling method provided by the above-mentioned method embodiments. The flow shop scheduling method may include: obtaining the initial arrangement sequence and initial maximum completion time of all workpieces to be processed based on a heuristic algorithm; obtaining a target combination sequence from the initial arrangement sequence, the target combination sequence including at least one target combination subsequence, and the target combination subsequence being at least two adjacent sequences in the initial arrangement sequence; inserting the target combination sequence into all possible new positions in the remaining sequence in sequence, and calculating the maximum completion time of the temporary arrangement sequence obtained each time, until all target combination sequences are traversed, and the remaining sequence is the arrangement sequence after removing the target combination sequence from the initial arrangement sequence; obtaining the maximum completion time of all temporary arrangement sequences and the minimum maximum completion time among the initial maximum completion times, and determining the arrangement sequence corresponding to the minimum maximum completion time as the production scheduling plan for the workpieces to be processed.

[0101] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the flow shop scheduling method provided by the above-mentioned method embodiments. The flow shop scheduling method may include: obtaining the initial arrangement sequence and initial maximum completion time of all workpieces to be processed based on a heuristic algorithm; obtaining a target combination sequence from the initial arrangement sequence, wherein the target combination sequence includes at least one target combination subsequence, and the target combination subsequence is at least two adjacent sequences in the initial arrangement sequence; inserting the target combination sequence into all possible new positions in the remaining sequence in sequence, and calculating the maximum completion time of the temporary arrangement sequence obtained each time, until all target combination sequences are traversed, and the remaining sequence is the arrangement sequence after removing the target combination sequence from the initial arrangement sequence; obtaining the maximum completion time of all temporary arrangement sequences and the minimum maximum completion time among the initial maximum completion times, and determining the arrangement sequence corresponding to the minimum maximum completion time as the production scheduling plan for the workpieces to be processed.

[0102] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0103] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, or of course, by hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the existing technology can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or certain parts of the embodiments.

[0104] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A flow shop scheduling method, characterized in that: include: Obtain the initial arrangement sequence and initial maximum completion time of all workpieces to be processed based on a heuristic algorithm; Acquire a target combination sequence from the initial permutation sequence, wherein the target combination sequence includes at least one target combination subsequence, and the target combination subsequence is at least two adjacent sequences in the initial permutation sequence; Inserting the target combination sequence into all possible new positions in the remaining sequence in sequence, and calculating the maximum completion time of each temporary permutation sequence obtained, until all target combination sequences are traversed, and the remaining sequence is the permutation sequence after removing the target combination sequence from the initial permutation sequence; Obtaining the minimum maximum completion time among the maximum completion times of all temporary arrangement sequences and the initial maximum completion times, and determining the arrangement sequence corresponding to the minimum maximum completion time as the production scheduling plan for the workpiece to be processed; The acquiring of a target combination sequence from the initial permutation sequence comprises: Selecting at least two adjacent sequences from the initial permutation sequence and combining them to obtain a first combined sequence; Selecting at least two adjacent sequences from the permutation sequence after removing the first combination sequence from the initial permutation sequence and combining them to obtain a second combination sequence; The first combination sequence and the second combination sequence are permuted and combined, and the target combination sequence is determined based on the permutation and combination result.

2. The flow shop scheduling method according to claim 1, characterized in that: Determining the target combination sequence based on the permutation and combination results includes: At least one of the permutation and combination results is determined as the target combination sequence.

3. The flow shop scheduling method according to claim 1, characterized in that: The method of obtaining the initial arrangement sequence and the initial maximum completion time of all workpieces to be processed based on the heuristic algorithm includes: Obtain an initial job list, wherein the initial job list includes the total processing time of each workpiece to be processed on all processing equipment; A heuristic algorithm is used to solve the initial solution of the initial job list to obtain the initial arrangement sequence and initial maximum completion time of all workpieces to be processed.

4. The flow shop scheduling method according to claim 1, characterized in that: The heuristic algorithm is the NEH algorithm.

5. A flow shop scheduling device, characterized in that: include: A first acquisition module is used to acquire an initial arrangement sequence and an initial maximum completion time of all workpieces to be processed based on a heuristic algorithm; A second acquisition module is configured to acquire a target combination sequence from the initial permutation sequence, wherein the target combination sequence includes at least one target combination subsequence, and the target combination subsequence is at least two adjacent sequences in the initial permutation sequence; a calculation module, configured to sequentially insert the target combination sequence into all possible new positions in the remaining sequence and calculate the maximum completion time of each temporary permutation sequence obtained until all target combination sequences are traversed, wherein the remaining sequence is the permutation sequence after removing the target combination sequence from the initial permutation sequence; a determination module, configured to obtain the minimum maximum completion time among the maximum completion times of all temporary arrangement sequences and the initial maximum completion times, and determine the arrangement sequence corresponding to the minimum maximum completion time as the production scheduling plan for the workpiece to be processed; The acquiring of a target combination sequence from the initial permutation sequence comprises: Selecting at least two adjacent sequences from the initial permutation sequence and combining them to obtain a first combined sequence; Selecting at least two adjacent sequences from the permutation sequence after removing the first combination sequence from the initial permutation sequence and combining them to obtain a second combination sequence; The first combination sequence and the second combination sequence are permuted and combined, and the target combination sequence is determined based on the permutation and combination result.

6. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the flow shop scheduling method according to any one of claims 1 to 4 is implemented.

7. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the flow shop scheduling method according to any one of claims 1 to 4 is implemented.

8. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the flow shop scheduling method according to any one of claims 1 to 4 is implemented.

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