Production scheduling plan generation method and system, electronic device and readable storage medium

Abstract

This invention relates to the field of production management technology and discloses a production scheduling plan generation method, system, electronic device, and readable storage medium. The method involves repeatedly sorting production order blocks corresponding to each product type to obtain multiple production order block sequences. The order of production orders for each product is constrained according to product type by set sorting constraints. Based on preset satisfaction values ​​corresponding to the sorting constraints, a sequence satisfaction value is determined for each production order block sequence. This allows for the determination of a target sequence from the production order block sequences, and the generation of a production schedule based on the target sequence. By fully considering the product type of the orders during production order scheduling, the utilization rate of production resources is improved, thereby increasing production efficiency.

Description

Technical Field

[0001] This invention relates to the field of production management technology, and in particular to a production scheduling plan generation method, system, electronic device, and readable storage medium. Background Technology

[0002] In the automobile manufacturing process, various problems, such as insufficient stockpiling of raw materials or parts, overly idealistic allocation of manpower or materials, and errors in production department capacity estimation, lead to significant waste in vehicle production costs, high manufacturing costs, and low production efficiency. To address these issues, existing enterprises pre-allocate production time and resources for product production orders, generating corresponding production schedules to control production costs, achieve reasonable production efficiency, and conduct production scientifically, rationally, and leanly.

[0003] However, since the types of products produced by production orders may differ, the required production materials, equipment, and production lines will also differ. The existing production scheduling plan does not take into account the corresponding product types of each order when arranging the production order sequence. The production scheduling plan is chaotic and disorderly, resulting in problems such as the need to change production materials according to the product type of the order when producing different production orders. This leads to the underutilization of production materials and low production efficiency. Summary of the Invention

[0004] To provide a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. This summary is not intended as a general commentary, nor is it intended to identify key / important components or describe the scope of protection of these embodiments, but rather as a prelude to the detailed description that follows.

[0005] In view of the shortcomings of the prior art described above, the present invention discloses a production scheduling plan generation method, system, electronic device and readable storage medium to improve the utilization rate of production materials and thus improve production efficiency.

[0006] This invention discloses a production scheduling plan generation method, comprising: obtaining a set of production scheduling order blocks, wherein the production scheduling order blocks include multiple product types and at least one production scheduling order block corresponding to each product type, the production scheduling order blocks being obtained by dividing the product production orders corresponding to the product types; obtaining multiple production scheduling order block sequences by sorting each of the production scheduling order blocks multiple times, and setting a sorting constraint table, wherein the sorting constraint table includes multiple sorting constraints and preset satisfaction values ​​corresponding to each sorting constraint, the sorting constraints being used to constrain the order between each of the product production orders according to the product type; determining the sequence satisfaction value corresponding to each production scheduling order block sequence according to the sorting constraint table, and determining a target sequence from the production scheduling order block sequences according to the sequence preset satisfaction value, wherein if any production scheduling order block sequence satisfies any sorting constraint, the preset satisfaction value corresponding to the sorting constraint is determined as the target value corresponding to the production scheduling order block sequence, the sequence satisfaction value corresponding to the production scheduling order block sequence being calculated by the target value corresponding to the production scheduling order block sequence; and determining the production schedule corresponding to each product production order according to the order of the product production orders in the target sequence.

[0007] Optionally, production scheduling order blocks are determined by the following method: obtaining a set of product production orders, the set of product production orders including product production orders corresponding to each product type; determining the quantity of all production scheduling order blocks as the total number of blocks, determining the quantity of production scheduling order blocks corresponding to any product type as the number of single-type blocks, and determining the quantity of product production orders in the production scheduling order blocks as the single-block order capacity; establishing partitioning constraints to constrain the single-type block quantity and the single-block order capacity, calculating the minimum value of the total number of blocks according to the partitioning constraints, and determining the single-type block quantity and single-block order capacity corresponding to the minimum value when the total number of blocks is at the minimum value; partitioning the product production orders corresponding to each product type according to the single-type block quantity and single-block order capacity corresponding to the minimum value to obtain production scheduling order blocks corresponding to each product type.

[0008] Optionally, the product type includes multiple production attributes, including at least one of vehicle model attributes, paint color attributes, export country attributes, and vehicle power attributes.

[0009] Optionally, the partitioning constraint includes at least one of the following formulas: In the formula, TN represents the quantity of all product types, and GN represents the quantity of all product types. t Let x be the number of single-type blocks for the t-th product type. tg For the single-block order capacity of the g-th production order block in the t-th product type, ON MAXFor the quantity of production orders for all products, ON t Let be the number of production orders for all products corresponding to the t-th product type. The maximum value of the preset block corresponding to the t-th product type. This represents the minimum value of a preset single-piece order for the t-th product type. y represents the maximum preset single-piece order value for the t-th product type. p Let p be the number of product production orders corresponding to the p-th production attribute. The minimum value of the preset attribute order corresponding to the p-th production attribute. This represents the maximum value of the preset attribute order corresponding to the p-th production attribute.

[0010] Optionally, multiple production scheduling order block sequences are obtained by sorting each of the production scheduling order blocks multiple times, including: obtaining production process information, the production process information including multiple production nodes arranged in production order and the production workshop corresponding to each production node; determining any production workshop as the target workshop, randomly sorting each of the production scheduling order blocks a preset number of times to obtain a subsequence set corresponding to the target workshop, wherein the subsequence set includes the preset number of order subsequences; and obtaining multiple production scheduling order block sequences by combining the order subsequences corresponding to each production workshop multiple times, wherein the production scheduling order block sequence includes any order subsequence of each of the production workshops.

[0011] Optionally, determining the target sequence from the production scheduling order block sequence based on the preset satisfaction value of the sequence includes: calculating the optimal satisfaction value based on all preset satisfaction values ​​in the sorting constraint table; determining each production scheduling order block sequence as a baseline solution space; randomly swapping a portion of the production scheduling order blocks in the baseline sequence; determining the swapped baseline solution space as a comparison solution space, wherein the production scheduling order block sequences in the baseline solution space are determined as the baseline sequence; in response to obtaining the comparison solution space, determining the baseline satisfaction value corresponding to the baseline solution space based on the sequence satisfaction value corresponding to each production scheduling order block sequence in the baseline solution space, and determining the comparison satisfaction value corresponding to the comparison solution space based on the sequence satisfaction value corresponding to each production scheduling order block sequence in the comparison solution space; if the comparison satisfaction value is greater than the baseline satisfaction value, updating the baseline solution space based on the comparison solution space, and performing a process on the production scheduling order blocks in the updated portion of the baseline sequence. Randomly swapping values ​​yields a new comparison solution space. If the comparison satisfaction value is less than or equal to the benchmark satisfaction value, the number of consecutive occurrences of the comparison satisfaction value being less than or equal to the benchmark satisfaction value is counted. If the number of consecutive occurrences is less than or equal to a preset threshold, an updated solution space is randomly selected from the benchmark solution space and the comparison solution space according to the space selection probability. The benchmark solution space is updated according to the selected updated solution space, and the production scheduling order blocks in a portion of the updated benchmark sequence are randomly swapped to obtain a new comparison solution space. The space selection probability represents the probability of selecting the comparison solution space, and the space selection probability is calculated based on the first difference between the comparison satisfaction value and the optimal satisfaction value, and the second difference between the benchmark satisfaction value and the optimal satisfaction value. If the number of consecutive occurrences is greater than the preset threshold, the benchmark sequence with the highest sequence satisfaction value in the benchmark solution space is determined as the target sequence.

[0012] Optionally, determining the production schedule corresponding to each product production order based on the order of product production orders in the target sequence includes: the production workshop includes a welding workshop, a painting workshop, and a final assembly workshop; obtaining the transportation time period of the welding production line in the welding workshop, the transportation time period of the painting production line in the painting workshop, the transportation time period of the final assembly production line in the final assembly workshop, the first transfer time period between the welding workshop and the painting workshop, and the second transfer time period between the painting workshop and the final assembly workshop; assigning order numbers to each product production order according to the order of product production orders in the target sequence; identifying any product production order as a pending production order; determining the welding start-up time point of the pending production order based on the preset welding frequency of the welding workshop and the order number of the pending production order; determining the welding off-line time point of the pending production order based on the welding start-up time point and the transportation time period of the welding production line; determining a first time point based on the welding off-line time point and the first transfer time period, and determining the painting start-up time point of the pending production order in the painting workshop based on the previous product production order. The first time point is determined by the line sequence time point and the preset coating frequency of the coating workshop, and the maximum value between the first time point and the second time point is determined as the coating start time point of the order to be produced. The second time point is determined by the coating start time point of the order to be produced and the transportation time period of the coating production line. The third time point is determined by the coating end time point and the second transfer time period, and by the assembly start time point of the previous product production order in the final assembly workshop, and the assembly time point of the final assembly workshop. The fourth time point is determined by the preset final assembly frequency, and the maximum value between the third time point and the fourth time point is determined as the final assembly start time point of the order to be scheduled for production; the final assembly end time point of the order to be scheduled for production is determined according to the final assembly start time point of the order to be scheduled for production and the transportation time period of the final assembly production line; the production schedule of the order to be scheduled for production is generated according to at least one of the welding start time point, welding start time point, painting start time point, painting end time point, final assembly start time point, and final assembly end time point of the order to be scheduled for production.

[0013] This invention discloses a production scheduling plan generation system, comprising: an acquisition module, configured to acquire a set of production scheduling order blocks, wherein each production scheduling order block includes multiple product types and at least one production scheduling order block corresponding to each product type, and the production scheduling order blocks are obtained by dividing the production orders corresponding to the product types; and a sorting module, configured to obtain multiple production scheduling order block sequences by sorting each of the production scheduling order blocks multiple times, and to set a sorting constraint table, wherein the sorting constraint table includes multiple sorting constraints and preset satisfaction values ​​corresponding to each sorting constraint, and the sorting constraints are used to adjust the order between each of the product production orders according to the product type. The order is constrained; a determination module is used to determine the sequence satisfaction value corresponding to each production order block sequence according to the sorting constraint table, and to determine the target sequence from the production order block sequence according to the preset satisfaction value of the sequence, wherein the sequence satisfaction value corresponding to the production order block sequence is calculated by calculating the target value corresponding to the production order block sequence. If any production order block sequence satisfies any sorting constraint condition, the preset satisfaction value corresponding to the sorting constraint condition is determined as the target value corresponding to the production order block sequence; a production scheduling module is used to determine the production plan corresponding to the product production order according to the order of the product production orders in the target sequence.

[0014] The present invention discloses an electronic device, comprising: a processor and a memory; the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory to cause the electronic device to perform the above-described method.

[0015] The present invention discloses a computer-readable storage medium having a computer program stored thereon: when the computer program is executed by a processor, it implements the above-described method.

[0016] The beneficial effects of this invention are:

[0017] By repeatedly sorting the production order blocks corresponding to each product type, multiple production order block sequences are obtained. The order of production orders is then constrained by product type using set sorting constraints. Based on preset satisfaction values ​​corresponding to the sorting constraints, a sequence satisfaction value is determined for each production order block sequence. This allows for the determination of a target sequence from the production order block sequences, and the generation of a production plan based on the target sequence. In this way, by using a set sorting constraint table to constrain the order of production orders by product type, and visualizing the rationality of the order through preset satisfaction values ​​corresponding to the sorting constraints, a target sequence is determined and a production plan is generated based on the sequence satisfaction values ​​corresponding to each production order block sequence. This approach fully considers the product type of the orders when scheduling production orders, improving the utilization rate of production resources and thus increasing production efficiency.

[0018] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0019] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort. In the drawings:

[0020] Figure 1 This is a flowchart illustrating a production schedule generation method in one embodiment of this disclosure;

[0021] Figure 2 This is a schematic diagram of the structure of a production scheduling order block in an embodiment of this disclosure;

[0022] Figure 3 This is a flowchart illustrating the method for determining a target sequence in an embodiment of this disclosure;

[0023] Figure 4 This is a schematic diagram of the structure of a production scheduling system in an embodiment of the present invention;

[0024] Figure 5 This is a schematic diagram of the structure of an electronic device in an embodiment of the present invention. Detailed Implementation

[0025] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, unless otherwise specified, the following embodiments and sub-samples in the embodiments can be combined with each other.

[0026] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Therefore, the drawings only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0027] In the following description, numerous details are explored to provide a more thorough explanation of embodiments of the invention. However, it will be apparent to those skilled in the art that embodiments of the invention may be practiced without these specific details. In other embodiments, well-known structures and devices are shown in block diagram form rather than in detail to avoid obscuring embodiments of the invention.

[0028] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this disclosure described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion.

[0029] Unless otherwise stated, the term "multiple" means two or more.

[0030] In this embodiment of the disclosure, the character " / " indicates that the objects before and after it are in an "or" relationship. For example, A / B means: A or B.

[0031] The term "and / or" describes an association between objects, indicating that three relationships can exist. For example, A and / or B means: A or B, or A and B.

[0032] Combination Figure 1 As shown in the embodiments of this disclosure, a production scheduling plan generation method is provided, including:

[0033] Step S101: Obtain the production scheduling order block set;

[0034] The production scheduling order block includes multiple product types and at least one production scheduling order block corresponding to each product type. The production scheduling order block is obtained by dividing the product production orders corresponding to the product types.

[0035] Step S102: Obtain multiple production order block sequences by sorting each production order block multiple times, and set a sorting constraint table;

[0036] The sorting constraint table includes multiple sorting constraints and preset satisfaction values ​​for each sorting constraint. The sorting constraints are used to constrain the order of production orders for each product based on the product type.

[0037] Step S103: Determine the sequence satisfaction value corresponding to each production scheduling order block sequence according to the sorting constraint table, and determine the target sequence from the production scheduling order block sequence according to the preset sequence satisfaction value;

[0038] If any production scheduling order block sequence satisfies any sorting constraint, then the preset satisfactory value corresponding to the sorting constraint is determined as the target value corresponding to the production scheduling order block sequence.

[0039] Among them, the sequence satisfaction value corresponding to the production scheduling order block sequence is obtained by calculating the target value corresponding to the production scheduling order block sequence;

[0040] Step S104: Determine the production schedule corresponding to the product production order based on the order of the product production orders in the target sequence.

[0041] The production scheduling method provided in this embodiment involves sorting the production order blocks corresponding to each product type multiple times to obtain multiple production order block sequences. The order of production orders is then constrained by set sorting constraints based on product type. A sequence satisfaction value is determined for each production order block sequence based on a preset satisfaction value corresponding to the sorting constraints. This allows for the determination of a target sequence from the production order block sequences, and the generation of a production schedule based on the target sequence. In this way, by using a set sorting constraint table to constrain the order of production orders based on product type, and visualizing the rationality of the order through preset satisfaction values ​​corresponding to the sorting constraints, the target sequence is determined and a production schedule is generated based on the sequence satisfaction value corresponding to each production order block sequence. This approach fully considers the product type of the orders when scheduling production orders, improving the utilization rate of production resources and thus increasing production efficiency.

[0042] Optionally, the product type includes multiple production attributes, including at least one of the following: vehicle model attribute, paint color attribute, export country attribute, and vehicle power attribute.

[0043] Optionally, the production schedule corresponding to the product production order includes the production schedule of three production workshops, including the welding workshop, the painting workshop and the final assembly workshop.

[0044] Optionally, the sorting constraints include hard constraints and soft constraints. Hard constraints include "the paint color attribute of the last production order on the first day is the same as the paint color attribute of the first production order on the second day", "production orders with the same export country attribute in the final assembly workshop must be consecutive", and "the number of processing production orders cached in previous production workshops in each production workshop must be less than a preset threshold". Soft constraints include "production orders with some production attributes are not arranged adjacently", "production orders with some production attributes are arranged adjacently", "there is a preset number of production order intervals between production orders with some production attributes", "the number of adjacent arrangement of production orders with some production attributes is within a preset range", "production orders with some production attributes have other specified production attributes", and "the number of times the production workshop switches product types is less than a preset switching threshold".

[0045] This allows for a rapid, complete, and accurate analysis of how automated scheduling results meet various production constraints, yielding the constraint satisfaction rate for each condition. Business personnel can manually adjust the production sequence of one or more workshops based on the satisfaction rate and actual business needs. This invention can recalculate the production sequence according to the manually adjusted order, ensuring that it meets both specific business sequencing requirements and overall production constraints.

[0046] Optionally, before determining the sequence satisfaction value corresponding to each production order block sequence according to the sorting constraint table, the method further includes: if any production attribute or product type appearing in any sorting constraint does not exist or has only one value in the obtained product production order, then the sorting constraint is regarded as an invalid condition; and the invalid condition is deleted from the sorting constraint table.

[0047] In this way, by standardizing the analysis of the relationship between the constraints of automobile production and the actual production and manufacturing scenario, and through standardized data analysis and processing, we can understand the actual situation of production orders from the whole to the individual parts, and from the comprehensive to the detailed. This will help us grasp the logical relationship between order information and production constraints, which is conducive to verifying the rationality and feasibility of the constraints.

[0048] Optionally, production scheduling order blocks are determined using the following method: A set of product production orders is obtained, including production orders corresponding to each product type; the quantity of all production scheduling order blocks is determined as the total number of blocks; the quantity of production scheduling order blocks corresponding to any product type is determined as the number of blocks per type; the quantity of production orders within a production scheduling order block is determined as the capacity of a single block; partitioning constraints are established to constrain the number of blocks per type and the capacity of a single block; the minimum value of the total number of blocks is calculated based on the partitioning constraints; and the minimum value of the total number of blocks is determined when the total number of blocks is at its minimum. The production orders corresponding to each product type are then partitioned based on the minimum value of the number of blocks per type and the capacity of a single block, resulting in production scheduling order blocks for each product type.

[0049] Combination Figure 2 As shown, this embodiment of the disclosure provides a production scheduling order block, wherein product production orders 1, 2, 3, 4, 5, 6, 7, and 8 all belong to product type A; product production orders 1, 2, 3, 4, and 5 are divided into production scheduling order block B, and product production orders 6, 7, and 8 are divided into production scheduling order block C; the number of single-type blocks for product type A is 2 production scheduling order blocks, the single-block order capacity of production scheduling order block B is 5 product production orders, and the single-block order capacity of production scheduling order block C is 3 product production orders.

[0050] In some embodiments, the partitioning constraints and objective function are passed to the GLPK (GNU Linear Programming Kit) integer programming solver. The GLPK integer programming solver calculates the minimum value of the total number of blocks and determines the number of single-type blocks and the single-block order capacity corresponding to the minimum value when the total number of blocks is at its minimum.

[0051] In some embodiments, the resulting production scheduling order blocks are shown in Table 1. Product type 1 has one production scheduling order block with an order quantity of 15, product type 3 has four production scheduling order blocks with an order quantity of 8, product type 4 has two production scheduling order blocks with an order quantity of 10, and product type 6 has one production scheduling order block with an order quantity of 17.

[0052] Table 1

[0053] Size Product Type 1 Product Type 3 Product Type 4 Product Type 6 8 4 10 2 15 1 17 1

[0054] Optionally, the partitioning constraints include at least one of the following formulas:

[0055]

[0056]

[0057]

[0058]

[0059]

[0060] In the formula, TN represents the quantity of all product types, and GN represents the quantity of all product types. t Let x be the number of single-type blocks for the t-th product type. tg For the single-block order capacity of the g-th production order block in the t-th product type, ON MAX For the quantity of production orders for all products, ON t Let be the number of production orders for all products corresponding to the t-th product type. The maximum value of the preset block corresponding to the t-th product type. This represents the minimum value of a preset single-piece order for the t-th product type. y represents the maximum preset single-piece order value for the t-th product type. p Let p be the number of product production orders corresponding to the p-th production attribute. The minimum value of the preset attribute order corresponding to the p-th production attribute. This represents the maximum value of the preset attribute order corresponding to the p-th production attribute.

[0061] Optionally, The production quantity used to represent product production orders should be less than or equal to the total number of all product production orders.

[0062] Optionally, The production scheduling quantity used to characterize a product production order for any product type should be less than or equal to the order quantity of product production orders for that product type.

[0063] Optionally, The number of production order blocks used to represent any product type should be less than or equal to the maximum preset block size for that product type.

[0064] Optionally, In the production scheduling order block representing any product type, the single order capacity of the product production order should be within the preset first order quantity range.

[0065] Optionally, For any given production attribute, the number of production orders for the corresponding product should fall within a preset second order quantity range.

[0066] Optionally, multiple production scheduling order block sequences are obtained by sorting each production scheduling order block multiple times, including: obtaining production process information, which includes multiple production nodes arranged in production order and the production workshop corresponding to each production node; determining any production workshop as the target workshop, randomly sorting each production scheduling order block a preset number of times to obtain a subsequence set corresponding to the target workshop, wherein the subsequence set includes a preset number of order subsequences; and obtaining multiple production scheduling order block sequences by combining the order subsequences corresponding to each production workshop multiple times, wherein the production scheduling order block sequence includes any order subsequence of each production workshop.

[0067] In some embodiments, the fixed annealing principle is used to determine the target sequence from the production order block sequence according to the preset satisfaction value of the sequence. The fixed annealing principle is to slowly cool the high-temperature object, so that the internal energy of the particles inside gradually decreases, the activity decreases, and the range of activity gradually decreases. That is, it randomly searches and walks in the possible solution space. Using the Metropolis sampling criterion, it selects the solution with a larger target value in the neighborhood with a certain probability, so that the random walk gradually converges. When the solid is cooled down or reaches equilibrium and stability, the position of the particles is fixed, so that the random walk gradually converges, thereby achieving global optimization and obtaining the optimal solution.

[0068] Optionally, determining the target sequence from the production scheduling order block sequence based on the preset satisfaction value of the sequence includes: calculating the optimal satisfaction value based on all preset satisfaction values ​​in the sorting constraint table; determining each production scheduling order block sequence as a baseline solution space, randomly swapping a portion of the production scheduling order blocks in the baseline sequence, and determining the swapped baseline solution space as a comparison solution space, wherein the production scheduling order block sequence in the baseline solution space is determined as the baseline sequence; in response to obtaining the comparison solution space, determining the baseline satisfaction value corresponding to the baseline solution space based on the sequence satisfaction value corresponding to each production scheduling order block sequence in the baseline solution space, and determining the comparison satisfaction value corresponding to the comparison solution space based on the sequence satisfaction value corresponding to each production scheduling order block sequence in the comparison solution space; if the comparison satisfaction value is greater than the baseline satisfaction value, updating the baseline solution space based on the comparison solution space, and adjusting the production scheduling order blocks in a portion of the updated baseline sequence. Random swapping is performed to obtain a new comparative solution space. If the comparative satisfaction value is less than or equal to the benchmark satisfaction value, the number of consecutive occurrences of the comparative satisfaction value being less than or equal to the benchmark satisfaction value is counted. If the number of consecutive occurrences is less than or equal to a preset threshold, an updated solution space is randomly selected from the benchmark solution space and the comparative solution space according to the space selection probability. The benchmark solution space is updated according to the selected updated solution space, and the production scheduling order blocks in a portion of the updated benchmark sequence are randomly swapped to obtain a new comparative solution space. The space selection probability represents the probability of selecting a comparative solution space, and the space selection probability is calculated based on the first difference between the comparative satisfaction value and the optimal satisfaction value, and the second difference between the benchmark satisfaction value and the optimal satisfaction value. If the number of consecutive occurrences is greater than the preset threshold, the benchmark sequence with the highest sequence satisfaction value in the benchmark solution space is determined as the target sequence.

[0069] Combination Figure 3 As shown, this disclosure provides a method for determining a target sequence, including:

[0070] Step S301: Calculate the optimal satisfaction value based on all preset satisfaction values ​​in the sorting constraint table;

[0071] Step S302: Determine each production scheduling order block sequence as the baseline solution space;

[0072] Among them, the production scheduling order block sequence in the benchmark solution space is determined as the benchmark sequence;

[0073] Step S303: Randomly swap the production scheduling order blocks in a portion of the baseline sequence, and determine the swapped baseline solution space as the comparison solution space;

[0074] Step S304: Determine the benchmark satisfaction value corresponding to the benchmark solution space based on the sequence satisfaction value corresponding to each production scheduling order block sequence in the benchmark solution space;

[0075] Step S305: Determine the comparison satisfaction value corresponding to the comparison solution space based on the sequence satisfaction value corresponding to each production scheduling order block sequence in the comparison solution space;

[0076] Step S306: Determine whether the comparison satisfaction value is greater than the benchmark satisfaction value. If yes, proceed to step S307; otherwise, proceed to step S308.

[0077] Step S307: Update the benchmark solution space according to the comparison solution space, then proceed to step S303;

[0078] Step S308: Count the number of consecutive occurrences of the satisfaction value being less than or equal to the benchmark satisfaction value;

[0079] Step S309: Does the number of consecutive occurrences exceed a preset threshold? If yes, proceed to step S312; otherwise, proceed to step S310.

[0080] Step S310: Randomly select an updated solution space from the baseline solution space and the comparison solution space according to the spatial selection probability;

[0081] The spatial selection probability is calculated based on the first difference between the comparative satisfactory value and the optimal satisfactory value, and the second difference between the benchmark satisfactory value and the optimal satisfactory value.

[0082] Step S311: Update the baseline solution space according to the selected updated solution space, then proceed to step S303;

[0083] Step S312: Determine the benchmark sequence with the highest sequence satisfaction value in the benchmark solution space as the target sequence.

[0084] Optionally, through Determine the spatial selection probability, where θ is the spatial selection probability, Δp is the first difference between the comparative satisfactory value and the optimal satisfactory value, and p is the second difference between the benchmark satisfactory value and the optimal satisfactory value.

[0085] In some embodiments, if the space selection probability is greater than the interval [0,1), then the comparison solution space is used as the updated solution space.

[0086] In some embodiments, the welding workshop, painting workshop, and final assembly workshop each have 100 order subsequences, where each production scheduling order block has a unique integer code. By combining the order subsequences corresponding to each production workshop multiple times, 100 production scheduling order block sequences are obtained. Based on the production scheduling order block sequences, a baseline solution space is determined. Twenty of these sequences are randomly selected, permuted, interchanged, and derived to form 100 new production scheduling order block sequences, resulting in a comparative solution space. Since the comparative solution space is generated only by the transformed part, the comparative satisfaction value is calculated incrementally. The first difference between the comparative satisfaction value and the optimal satisfaction value is calculated as Δp, and the second difference between the baseline satisfaction value and the optimal satisfaction value is calculated as p. The Metropolis acceptance criterion is used as the judgment basis, where if Δp < p, the comparative solution space is accepted as the new baseline solution space; if Δp ≥ p, the space selection probability is used. Accept the comparative solution space as the new benchmark solution space; take the comparative solution space as the new benchmark solution space as one iteration, count the number of iterations, and if the second difference between the benchmark satisfactory value and the optimal satisfactory value cannot be further reduced after 10 iterations, then determine the target sequence from the benchmark satisfactory value.

[0087] Optionally, the production schedule corresponding to each product production order is determined according to the order of product production orders in the target sequence, including: the production workshops include a welding workshop, a painting workshop, and a final assembly workshop; the transportation time periods of the welding production line in the welding workshop, the painting production line in the painting workshop, the final assembly production line in the final assembly workshop, the first transfer time period between the welding workshop and the painting workshop, and the second transfer time period between the painting workshop and the final assembly workshop are obtained; order numbers are assigned to each product production order according to the order of product production orders in the target sequence; any product production order is identified as a pending production order; the welding start-up time of the pending production order is determined by the preset welding frequency of the welding workshop and the order number of the pending production order; the welding off-line time of the pending production order is determined by the welding start-up time and the welding production line transportation time period; the first time point is determined by the welding off-line time point and the first transfer time period, and the painting start-up time of the pending production order is determined by the previous product production order in the painting workshop. The second time point is determined by the pre-set painting frequency in the painting workshop and the first time point. The maximum value between the first and second time points is determined as the painting start time point for the order to be produced. The painting end time point for the order to be produced is determined based on the painting start time point and the transportation time period of the painting production line. The third time point is determined based on the painting end time point and the second transfer time period, and based on the final assembly start time point of the previous product production order in the final assembly workshop and the pre-set final assembly time point of the final assembly workshop. The frequency determines the fourth time point, and the maximum value between the third and fourth time points is determined as the final assembly line start time point for the orders to be scheduled for production. The final assembly line end time point for the orders to be scheduled for production is determined based on the final assembly line start time point and the transportation time period of the final assembly production line. The production schedule for the orders to be scheduled for production is generated based on at least one of the welding line start time point, the painting line start time point, the painting line end time point, the final assembly line start time point, and the final assembly line end time point.

[0088] Optionally, the welding start time of the order to be produced = the preset welding frequency of the welding workshop × the order number of the order to be produced.

[0089] Optionally, the welding off-line sequence time for orders awaiting production = welding on-line sequence time + welding production line transportation time.

[0090] Optionally, the painting start time of the order to be scheduled = max(welding end time + first transfer time period, painting start time of the previous product production order in the painting workshop + preset painting frequency of the painting workshop).

[0091] Optionally, the time point for the coating off-line sequence of the pending production order = the time point for the coating on-line sequence of the pending production order + the transportation time period of the coating production line.

[0092] Optionally, the assembly line start time of the order to be scheduled = max(painting line start time + second transfer time period, the assembly line start time of the previous product production order of the order to be scheduled in the final assembly workshop + the preset assembly frequency of the final assembly workshop).

[0093] Optionally, the final assembly line exit time of the pending production order = the final assembly line entry time of the pending production order + the transportation time of the final assembly production line.

[0094] In this way, by establishing an algorithm model to solve the production scheduling problem, the production order of each workshop can be automatically obtained, which greatly improves the scheduling efficiency and solves the problems faced by manual scheduling, such as insufficient professionalism, incomplete consideration of constraints, high scheduling difficulty, chaotic scheduling results, and low scheduling efficiency.

[0095] Combination Figure 4 As shown, this embodiment of the disclosure provides a production scheduling plan generation system, including an acquisition module 401, a sorting module 402, a determination module 403, and a production scheduling module 404. The acquisition module 401 is used to acquire a set of production scheduling order blocks, which includes multiple product types and at least one production scheduling order block corresponding to each product type. The production scheduling order blocks are obtained by dividing the product production orders corresponding to the product types. The sorting module 402 is used to obtain multiple production scheduling order block sequences by sorting each production scheduling order block multiple times, and to set a sorting constraint table. The sorting constraint table includes multiple sorting constraints and preset satisfaction values ​​corresponding to each sorting constraint. The sorting constraints are used to constrain the order between each product production order according to the product type. The determination module 403 is used to determine the sequence satisfaction value corresponding to each production scheduling order block sequence according to the sorting constraint table, and to determine the target sequence from the production scheduling order block sequence according to the sequence preset satisfaction value. The sequence satisfaction value corresponding to the production scheduling order block sequence is calculated by calculating the target value corresponding to the production scheduling order block sequence. If any production scheduling order block sequence satisfies any sorting constraint, the preset satisfaction value corresponding to the sorting constraint is determined as the target value corresponding to the production scheduling order block sequence. The production scheduling module 404 is used to determine the production plan corresponding to the product production order according to the order of the product production orders in the target sequence.

[0096] The production scheduling system provided in this embodiment sorts the production order blocks corresponding to each product type multiple times to obtain multiple production order block sequences. The order of production orders is then constrained by set sorting constraints based on product type. A sequence satisfaction value is determined for each production order block sequence based on a preset satisfaction value corresponding to the sorting constraints. This allows for the determination of a target sequence from the production order block sequences, and the generation of a production schedule based on the target sequence. In this way, by using a set sorting constraint table to constrain the order of production orders based on product type, and visualizing the rationality of the order through preset satisfaction values ​​corresponding to the sorting constraints, the target sequence is determined and a production schedule is generated based on the sequence satisfaction value corresponding to each production order block sequence. This approach fully considers the product type of the orders when scheduling production orders, improving the utilization rate of production resources and thus increasing production efficiency.

[0097] Figure 5 A schematic diagram of a computer system suitable for implementing the embodiments of this application is shown. It should be noted that... Figure 5 The computer system 500 of the electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0098] like Figure 5 As shown, the computer system 500 includes a Central Processing Unit (CPU) 501, which can perform various appropriate actions and processes, such as executing the methods described in the above embodiments, based on programs stored in Read-Only Memory (ROM) 502 or programs loaded from storage portion 508 into Random Access Memory (RAM) 503. The RAM 503 also stores various programs and data required for system operation. The CPU 501, ROM 502, and RAM 503 are interconnected via a bus 504. An Input / Output (I / O) interface 505 is also connected to the bus 504.

[0099] The following components are connected to I / O interface 505: an input section 506 including a keyboard, mouse, etc.; an output section 507 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card such as a LAN (Local Area Network) card, modem, etc. The communication section 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to I / O interface 505 as needed. Removable media 511, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 510 as needed so that computer programs read from them can be installed into storage section 508 as needed.

[0100] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program including a computer program for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 509, and / or installed from removable medium 511. When the computer program is executed by central processing unit (CPU) 501, it performs various functions defined in the system of this application.

[0101] It should be noted that the computer-readable medium shown in the embodiments of this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying a computer-readable computer program. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The computer program contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to wireless, wired, etc., or any suitable combination thereof.

[0102] This disclosure also provides a computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements any of the methods described in this embodiment.

[0103] The computer-readable storage medium in the embodiments of this disclosure will be understood by those skilled in the art: all or part of the steps of the above method embodiments can be implemented by hardware related to computer programs. The aforementioned computer program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disk, or optical disk.

[0104] The electronic device disclosed in this embodiment includes a processor, a memory, a transceiver, and a communication interface. The memory and the communication interface are connected to the processor and the transceiver and complete communication between them. The memory is used to store computer programs, the communication interface is used to perform communication, and the processor and the transceiver are used to run the computer programs, so that the electronic device performs the various steps of the above method.

[0105] In this embodiment, the memory may include random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage device.

[0106] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), graphics processing units (GPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0107] The foregoing description and accompanying drawings fully illustrate embodiments of this disclosure to enable those skilled in the art to practice them. Other embodiments may include structural, logical, electrical, procedural, and other changes. The embodiments represent only possible variations. Individual components and functions are optional unless explicitly required, and the order of operation may vary. Parts and subsamples of some embodiments may be included in or replace parts and subsamples of other embodiments. Moreover, the terminology used in this application is for describing embodiments only and is not intended to limit the claims. As used in the description of embodiments and claims, the singular forms “a,” “an,” and “the” are intended to equally include the plural forms unless the context clearly indicates otherwise. Similarly, the term “and / or” as used herein means including one or more of the associated listed items and all possible combinations thereof. Additionally, when used in this application, the term "comprise" and its variations "comprises" and / or "comprising" refer to the presence of stated subsamples, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other subsamples, wholes, steps, operations, elements, components, and / or groups thereof. Without further limitations, an element defined by the phrase "comprising a..." does not exclude the presence of other identical elements in the process, method, or apparatus that includes the element. In this document, each embodiment may focus on the differences from other embodiments, and similar or identical parts between embodiments can be referred to mutually. For methods, products, etc., disclosed in the embodiments, if they correspond to the method section disclosed in the embodiments, the relevant parts can be referred to the description of the method section.

[0108] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the embodiments of this disclosure. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0109] The methods and products (including but not limited to devices and equipment) disclosed in the embodiments herein can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of units may be merely a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some sub-samples may be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection of devices or units may be electrical, mechanical, or other forms. Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units may be selected to implement this embodiment according to actual needs. Furthermore, the functional units in the embodiments of this disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0110] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than that shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. In the descriptions corresponding to the flowcharts and block diagrams in the accompanying drawings, the operations or steps corresponding to different blocks may also occur in a different order than disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. Each block in a block diagram and / or flowchart, and combinations of blocks in a block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

Claims

1. A method for generating a production schedule, characterized in that, include: Obtain a set of production scheduling order blocks, wherein the production scheduling order blocks include multiple product types and at least one production scheduling order block corresponding to each product type, and the production scheduling order blocks are obtained by dividing the product production orders corresponding to the product types; The production scheduling order blocks are determined by the following method to obtain a product production order set, which includes product production orders corresponding to each product type; the number of all production scheduling order blocks is determined as the total number of blocks, the number of production scheduling order blocks corresponding to any product type is determined as the number of blocks of a single type, and the number of product production orders in the production scheduling order blocks is determined as the single block order capacity. Establish partitioning constraints to limit the number of blocks of the single type and the order capacity of the single block, calculate the minimum value of the total number of blocks based on the partitioning constraints, and determine the number of blocks of the single type and the order capacity of the single block corresponding to the minimum value when the total number of blocks is at the minimum value; The production orders for each product type are divided according to the number of single-type blocks and the single-block order capacity corresponding to the minimum value, so as to obtain the production scheduling order blocks corresponding to each product type. The product type includes multiple production attributes, including at least one of vehicle model attributes, paint color attributes, export country attributes, and vehicle power attributes. Multiple production order block sequences are obtained by sorting each production order block multiple times, and a sorting constraint table is set. The sorting constraint table includes multiple sorting constraints and preset satisfaction values ​​corresponding to each sorting constraint. The sorting constraints are used to constrain the order between production orders of each product according to the product type. The partitioning constraints include at least one of the following formulas. , , , , In the formula, For the quantity of all product types, For the first Number of single-type blocks for each product type For the first The first product type The capacity of a single production order block The quantity of production orders for all products, For the first The quantity of all product production orders corresponding to each product type For the first The maximum value of the preset block corresponding to each product type For the first Minimum preset order value for each product type For the first The preset maximum order value for each product type For the first The number of product production orders corresponding to each production attribute For the first Minimum value of preset attribute orders corresponding to each production attribute For the first The maximum value of a preset attribute order corresponding to a production attribute; The sequence satisfaction value corresponding to each production scheduling order block sequence is determined according to the sorting constraint table, and the target sequence is determined from the production scheduling order block sequence according to the sequence satisfaction value. If any production scheduling order block sequence satisfies any sorting constraint condition, the preset satisfaction value corresponding to the sorting constraint condition is determined as the target value corresponding to the production scheduling order block sequence. The sequence satisfaction value corresponding to the production scheduling order block sequence is calculated by calculating the target value corresponding to the production scheduling order block sequence. The production schedule corresponding to each product production order is determined based on the order of the product production orders in the target sequence.

2. The method according to claim 1, characterized in that, Multiple production order block sequences are obtained by sorting each of the aforementioned production order blocks multiple times, including: Obtain production process information, which includes multiple production nodes arranged in production sequence and the production workshop corresponding to each production node; Any production workshop is designated as the target workshop. Each production scheduling order block is randomly sorted a preset number of times to obtain a subsequence set corresponding to the target workshop. The subsequence set includes the preset number of order subsequences. By combining the order sub-sequences corresponding to each production workshop multiple times, multiple production scheduling order block sequences are obtained, wherein each production scheduling order block sequence includes any order sub-sequence of each production workshop.

3. The method according to claim 2, characterized in that, Determining the target sequence from the production scheduling order block sequence based on the sequence satisfaction value includes: The optimal satisfaction value is calculated based on all preset satisfaction values ​​in the sorting constraint table. Each of the production scheduling order block sequences is determined as the baseline solution space. A portion of the production scheduling order blocks in the baseline sequences are randomly interchanged. The interchanged baseline solution space is determined as the comparison solution space. The production scheduling order block sequences in the baseline solution space are determined as the baseline sequences. In response to obtaining the comparison solution space, the benchmark satisfaction value corresponding to the benchmark solution space is determined according to the sequence satisfaction value corresponding to each production scheduling order block sequence in the benchmark solution space, and the comparison satisfaction value corresponding to the comparison solution space is determined according to the sequence satisfaction value corresponding to each production scheduling order block sequence in the comparison solution space; If the comparison satisfaction value is greater than the benchmark satisfaction value, the benchmark solution space is updated according to the comparison solution space, and the production scheduling order blocks in a portion of the updated benchmark sequence are randomly swapped to obtain a new comparison solution space; If the comparison satisfaction value is less than or equal to the benchmark satisfaction value, then count the number of consecutive occurrences of the comparison satisfaction value being less than or equal to the benchmark satisfaction value; If the number of consecutive occurrences is less than or equal to a preset threshold, an updated solution space is randomly selected from the baseline solution space and the comparison solution space according to the space selection probability. The baseline solution space is updated according to the selected updated solution space, and the production scheduling order blocks in a portion of the updated baseline sequence are randomly swapped to obtain a new comparison solution space. The space selection probability represents the probability of selecting the comparison solution space, and the space selection probability is calculated based on the first difference between the comparison satisfaction value and the optimal satisfaction value, and the second difference between the baseline satisfaction value and the optimal satisfaction value. If the number of consecutive occurrences is greater than a preset threshold, then the benchmark sequence with the highest sequence satisfaction value in the benchmark solution space is determined as the target sequence.

4. The method according to claim 2, characterized in that, Determining the production schedule corresponding to each product production order based on the order of the product production orders in the target sequence includes: The production workshop includes a welding workshop, a painting workshop, and a final assembly workshop; The transportation time of the welding production line in the welding workshop, the transportation time of the painting production line in the painting workshop, the transportation time of the final assembly production line in the final assembly workshop, the first transfer time between the welding workshop and the painting workshop, and the second transfer time between the painting workshop and the final assembly workshop are obtained. Assign order numbers to each of the product production orders according to the order of the product production orders in the target sequence; Designate any product production order as a pending production order; The welding start-up time of the order to be produced is determined by the preset welding frequency of the welding workshop and the order number of the order to be produced. The welding off-line time of the pending production order is determined based on the welding on-line time and the transportation time of the welding production line. The first time point is determined based on the welding off-line time point and the first transfer time period. The second time point is determined based on the coating on-line time point of the previous product production order of the order to be scheduled in the coating workshop and the preset coating frequency of the coating workshop. The maximum value between the first time point and the second time point is determined as the coating on-line time point of the order to be scheduled. The coating off-line time of the pending production order is determined based on the coating start-up time of the pending production order and the transportation time of the coating production line. A third time point is determined based on the painting off-line time point and the second transfer time period. A fourth time point is determined based on the final assembly line start time point of the previous product production order of the order to be scheduled for production in the final assembly workshop and the preset final assembly frequency of the final assembly workshop. The maximum value of the third time point and the fourth time point is determined as the final assembly line start time point of the order to be scheduled for production. The final assembly line exit time of the order to be produced is determined based on the final assembly line start time of the order to be produced and the transportation time of the final assembly line. The production schedule for the pending production order is generated based on at least one of the following: welding start time, welding end time, painting start time, painting end time, final assembly start time, and final assembly end time.

5. A production scheduling plan generation system, characterized in that, include: The acquisition module is used to acquire a set of production scheduling order blocks, wherein the production scheduling order blocks include multiple product types and at least one production scheduling order block corresponding to each product type, and the production scheduling order blocks are obtained by dividing the product production orders corresponding to the product types. The acquisition module determines the production scheduling order block and acquires the product production order set by the following method: the product production order set includes the product production orders corresponding to each product type; the number of all production scheduling order blocks is determined as the total number of blocks; the number of production scheduling order blocks corresponding to any product type is determined as the number of blocks of a single type; and the number of product production orders in the production scheduling order block is determined as the single block order capacity. Establish partitioning constraints to limit the number of blocks of the single type and the order capacity of the single block, calculate the minimum value of the total number of blocks based on the partitioning constraints, and determine the number of blocks of the single type and the order capacity of the single block corresponding to the minimum value when the total number of blocks is at the minimum value; The production orders for each product type are divided according to the number of single-type blocks and the single-block order capacity corresponding to the minimum value, so as to obtain the production scheduling order blocks corresponding to each product type. The product type includes multiple production attributes, including at least one of vehicle model attributes, paint color attributes, export country attributes, and vehicle power attributes. The sorting module is used to obtain multiple production order block sequences by sorting each of the production order blocks multiple times, and to set a sorting constraint table, wherein the sorting constraint table includes multiple sorting constraints and preset satisfaction values ​​corresponding to each sorting constraint, and the sorting constraints are used to constrain the order between the production orders of each product according to the product type. The partitioning constraints include at least one of the following formulas. , , , , In the formula, For the quantity of all product types, For the first Number of single-type blocks for each product type For the first The first product type The capacity of a single production order block The quantity of production orders for all products, For the first The quantity of all product production orders corresponding to each product type For the first The maximum value of the preset block corresponding to each product type For the first Minimum preset order value for each product type For the first The preset maximum order value for each product type For the first The number of product production orders corresponding to each production attribute For the first Minimum value of preset attribute orders corresponding to each production attribute For the first The maximum value of a preset attribute order corresponding to a production attribute; The determining module is used to determine the sequence satisfaction value corresponding to each of the production scheduling order block sequences according to the sorting constraint table, and to determine the target sequence from the production scheduling order block sequences according to the sequence satisfaction value. The sequence satisfaction value corresponding to the production scheduling order block sequence is obtained by calculating the target value corresponding to the production scheduling order block sequence. If any production scheduling order block sequence satisfies any sorting constraint condition, the preset satisfaction value corresponding to the sorting constraint condition is determined as the target value corresponding to the production scheduling order block sequence. The production scheduling module is used to determine the production scheduling plan corresponding to the product production order based on the order of the product production orders in the target sequence.

6. An electronic device, characterized in that, include: Processor and memory; The memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory to cause the electronic device to perform the method as described in any one of claims 1 to 4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, it implements the method as described in any one of claims 1 to 4.

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