Production outsourcing situation-based high-end equipment development and batch production cooperative scheduling method

Abstract

The invention provides a production outsourcing situation-based high-end equipment development and batch production collaborative scheduling method and system, a storage medium and electronic equipment, and relates to the field of high-end equipment development and batch production collaborative scheduling. According to the method, the problem of collaborative scheduling of two stages of development and batch production of high-end equipment manufacturers is solved, the situation that orders are outsourced by the manufacturers is increased, and the actual requirements of development of high-end equipment enterprises are met. Aiming at the condition that manufacturers develop batch production by themselves, the maximum total profit of the manufacturers is taken as an optimization target, a self-developed batch production order set and corresponding development teams and production lines are acquired, and an outsourcing order set is determined accordingly. Besides, an improved iterative greedy algorithm is utilized to quickly and accurately obtain an approximate optimal solution of the problem, the solving result can meet the production requirements of high-end equipment manufacturers, the development and batch production efficiency of the high-end equipment is improved, and the total income of the high-end equipment manufacturers is increased.

Description

Technical Field

[0001] The present invention relates to the field of high-end equipment development and batch production coordinated scheduling, and in particular to a high-end equipment development and batch production coordinated scheduling method, system, storage medium and electronic equipment based on production outsourcing. Background Art

[0002] As high-end equipment with advanced technology and at the top of the manufacturing value chain, the market competition is fierce. In order to cope with the uncertain market environment and the increasing production costs, outsourcing has gradually become a means for high-end equipment companies to solve production and operation problems. In the case of production outsourcing, high-end equipment manufacturers entrust part of the orders to outsourcers to ensure that they have sufficient resources for product research and development and manufacturing batch production. However, the implementation of the outsourcing strategy will increase the difficulty of scheduling for high-end equipment manufacturers. On the one hand, manufacturers need to decide which orders to outsource, and on the other hand, manufacturers need to coordinate the development and batch production of the remaining orders.

[0003] In the related technologies, the existing R&D-batch production scheduling problem is mainly analyzed based on the traditional production model, that is, two-stage scheduling is carried out in chronological order, but the related problems fail to take into account the production outsourcing situation, resulting in the solution results failing to meet the actual needs of manufacturers. At the same time, the existing problems mainly use some precise algorithms and simulation algorithms when solving them, which leads to an increase in calculation time and the inability to quickly obtain the optimal solution, thus causing a waste of resources for high-end equipment manufacturers. Summary of the invention

[0004] 1. Technical issues to be solved

[0005] In view of the deficiencies in the prior art, the present invention provides a method, system, storage medium and electronic device for coordinated scheduling of high-end equipment development and batch production based on production outsourcing situations, which solves the technical problem that the prior art fails to take production outsourcing situations into consideration.

[0006] (II) Technical solution

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0008] A method for coordinated scheduling of high-end equipment development and batch production based on production outsourcing, comprising:

[0009] Obtain high-end equipment order information, manufacturer's R&D team and production line data;

[0010] An initialization population including a plurality of initial solutions is generated by adopting a three-segment coding rule based on the order layer, the research layer and the batch production layer; wherein, the order allocation sequence of the order layer of the initial solution is generated by comparing the outsourcing income of the order with the self-research batch production income;

[0011] Destroy each initial solution, compare the outsourcing revenue of the order with the revenue of self-developed batch production, and take maximizing the total revenue of the manufacturer as the optimization goal to obtain multiple new solutions;

[0012] Performing a local search and update on the orders for batch production by the manufacturer in the new solution;

[0013] Determine whether it is greater than the iteration termination temperature. If so, re-execute the local search and update operation until the condition is met; otherwise, output the global optimal solution, decode and obtain the self-developed batch production order set and its corresponding development team and production line, and combine the high-end equipment order information to obtain the outsourced order set.

[0014] Preferably, the three-stage coding rule based on the order layer, the research layer and the batch production layer is adopted to generate an initialization population including multiple initial solutions; including:

[0015] Based on the high-end equipment order information, an order allocation sequence of the order layer is generated in sequence, and the order index j=1 of the order allocation sequence is initialized;

[0016] Calculate the outsourcing revenue NP of order j oj NP aj ;

[0017] Compare Outsourcing BenefitsNP oj and self-developed batch production yield NP aj The size of NP oj ≥NP aj , outsource order j; otherwise, the manufacturer develops and batches it by itself and assigns it to the corresponding development team r and production line i;

[0018] Update the earliest start time min (CS jr ), and the earliest start time of batch production at production line i min(BT ij );

[0019] Let j = j + 1. If j is less than or equal to the total number of orders n, then recalculate the outsourcing revenue NP of order j. oj NP aj , until the conditions are met; otherwise, the population initialization is terminated.

[0020] Preferably, the outsourcing revenue NP of order j is oj NP aj The calculation method is as follows:

[0021] NP oj =u j -oc j(1)

[0022] NP aj =u j -max {FT j -d j ,0}·yc j -PC r ·YT jr -PC i ·PT ij (2)

[0023] Among them, u j represents the revenue of order j; oc j represents the outsourcing cost of order j;

[0024] Max is the maximization function; FT j represents the completion time of order j from the manufacturer to batch production; d j represents the delivery date of order j; yc j represents the overdue penalty cost per unit for order j; PC r represents the development cost of development team r; YT jr represents the development time of order j in development team r; PC i Batch production cost of production line j; PT ij Represents the batch production time of order j in production line i.

[0025] Preferably, the earliest start time min(CS jr ) and the earliest start time of batch production at production line i min(BT ij ) is calculated as follows:

[0026]

[0027]

[0028] Among them, min is the minimization function; CS jr indicates the start time of order j in development team r; It represents the time required for the development of the order before order j and which is in charge of the development team r;

[0029] BT ij represents the start time of order j in production line i; WT jr represents the completion time of order j in development team r; It indicates the time required to batch produce the order that is placed before order j and is handled by production line i.

[0030] Preferably, the method of performing a destruction operation on each initial solution, again comparing the outsourcing revenue of the order with the revenue of self-developed batch production, and taking maximizing the total revenue of the manufacturer as the optimization goal, obtaining multiple new solutions; includes:

[0031] Based on the initial solution x 0 The number of orders for self-developed batch production and the destruction rate θ, generate the corresponding number of position coordinates, remove the initial solution x 0 The orders at the corresponding positions in the , and their corresponding R&D teams and production lines, get an incomplete solution x ′ , and put the removed orders into the set of orders to be inserted δ;

[0032] Randomly select an order j from the set δ, remove it from the set and insert it into x ′ All possible positions in

[0033] Update the manufacturer's development and batch production completion time for each order after order j is inserted, and recalculate the self-development and batch production revenue NP for each order aj , if you develop and mass produce the profit NP aj Lower than outsourcing benefits NP oj , the order will be outsourced;

[0034] Calculate the total revenue TP of manufacturers at different insertion positions, and select the solution with the largest total revenue TP of manufacturers as the insertion solution for order j; the calculation method of the total revenue TP of manufacturers is as follows:

[0035]

[0036] Among them, s is the total number of research and development teams; m is the total number of production lines; X j is the decision variable;

[0037] Determine whether the set δ is an empty set. If not, go to S32 and select a new order j from the set δ. ′ Perform the insertion operation until the condition is met; if so, end the reconstruction operation and output the new solution x 1 .

[0038] Preferably, the following various neighborhood structures are designed to perform local search and update operations:

[0039] Neighborhood structure 1: define variable h1, randomly generate an integer in the interval [1,n] and assign it to h1. For the order allocation sequence PS of the order layer, determine whether the orders at the h1th position and the 1st position are both developed and batch produced by the manufacturer. If so, swap the order codes at the h1th position and the 1st position, otherwise, do not change;

[0040] Neighborhood Structure 2: Define variables h1 and h2. Randomly generate two integers in the interval [1, n], assign them to h1 and h2, such that h1 < h2. For the research team assignment sequence RS in the research and development layer, determine whether the orders at the h1-th position and the h2-th position are both for manufacturer research and development. If so, swap the order codes at the h1-th position and the h2-th position; otherwise, keep them unchanged.

[0041] Neighborhood Structure 3: Define variables h1 and h2. Randomly generate two integers in the interval [1, n], assign them to h1 and h2, such that h1 < h2. For the production line assignment sequence BS in the mass production layer, swap the order codes of the orders responsible for mass production by the manufacturer to the left of the h1-th position and to the right of the h2-th position.

[0042] Neighborhood Structure 4: Define variables h1, h2, and h3. Randomly generate three integers in the interval [1, n], assign them to h1, h2, and h3, such that h1 < h2 < h3. For the research team assignment sequence RS in the research and development layer, reverse the order codes of the orders responsible for mass production by the manufacturer to the left of the h1-th position and to the right of the h3-th position. For the production line assignment sequence BS in the mass production stage, reverse the order codes of the orders responsible for mass production by the manufacturer between the h1-th position and the h2-th position.

[0043] Preferably, the decoding rules include:

[0044] For the research team assignment sequence in the research and development layer, obtain the orders assigned to each research team. When multiple orders are assigned to research team r, compare the research times YT of different orders j in this research team r jr , select the order j with a longer research time for research first. If the research times of the orders are the same, then preferentially select the order j with a higher income u j for research;

[0045] For the production line assignment sequence in the mass production layer, obtain the orders assigned to each production line. When multiple orders are assigned to production line i, compare the earliest completion times min(WT jr ) of different orders j being developed, select the order j with the earliest development completion time for mass production. If the development completion times of the orders are the same, then preferentially select the order j with a higher income u j for mass production;

[0046] Combine the decoding results of the two parts to obtain the set of self-developed and mass-produced orders and the corresponding research teams and production lines.

[0047] A high-end equipment research and development and mass production collaborative scheduling system based on the production outsourcing scenario, including:

[0048] The acquisition module is used to obtain high-end equipment order information, manufacturer's research and development team and production line data;

[0049] An initialization module is used to generate an initialization population including a plurality of initial solutions by adopting a three-segment coding rule based on the order layer, the research layer and the batch production layer; wherein the order allocation sequence of the order layer of the initial solution is generated by comparing the outsourcing income of the order with the self-research and batch production income;

[0050] The comparison module is used to perform a destructive operation on each initial solution, and obtain multiple new solutions by comparing the outsourcing revenue of the order with the revenue of self-developed batch production, and taking maximizing the total revenue of the manufacturer as the optimization goal;

[0051] An updating module, used for performing local search and update on the orders for batch production of the manufacturer in the new solution;

[0052] The output module is used to determine whether it is greater than the iteration termination temperature. If so, the local search and update operation is re-executed until the conditions are met; otherwise, the global optimal solution is output, and the self-developed batch production order set and its corresponding development team and production line are decoded and obtained, and the outsourced order set is obtained in combination with the high-end equipment order information.

[0053] A storage medium stores a computer program for coordinated scheduling of high-end equipment development and batch production based on production outsourcing, wherein the computer program enables a computer to execute the high-end equipment development and batch production coordinated scheduling method as described above.

[0054] An electronic device, comprising:

[0055] One or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the programs include a method for executing the high-end equipment development and batch production coordinated scheduling method as described above.

[0056] (III) Beneficial effects

[0057] The present invention provides a method, system, storage medium and electronic device for coordinating the development and batch production of high-end equipment based on production outsourcing. Compared with the prior art, it has the following advantages:

[0058] Beneficial effects:

[0059] The present invention is aimed at the problem of coordinated scheduling of the two stages of R&D and batch production of high-end equipment manufacturers, and increases the situation where manufacturers outsource orders, which meets the actual needs of the development of high-end equipment enterprises. In view of the situation where manufacturers develop and batch produce by themselves, the optimization goal is to maximize the overall profit of the manufacturer, obtain the set of self-developed batch production orders and their corresponding R&D teams and production lines, and determine the set of outsourced orders accordingly. In addition, the improved iterative greedy algorithm is used to quickly and accurately obtain the approximate optimal solution to the problem. The solution can meet the production needs of high-end equipment manufacturers, improve the efficiency of high-end equipment development and batch production, and increase the total revenue of high-end equipment manufacturers. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0061] Figure 1 A block diagram of a method for coordinating the development and batch production of high-end equipment based on production outsourcing provided by an embodiment of the present invention;

[0062] Figure 2 A flowchart of an improved iterative greedy algorithm provided by an embodiment of the present invention;

[0063] Figure 3 A schematic diagram of a three-segment coding sequence based on order layer-development layer-batch production layer provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0064] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention are clearly and completely described. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0065] The embodiments of the present application provide a method, system, storage medium and electronic device for coordinating the development and batch production of high-end equipment based on production outsourcing, which solves the technical problem that the prior art fails to take production outsourcing into consideration, and provides a reference for the technical problem of quickly and accurately obtaining the optimal solution. That is, the method can quickly obtain an approximate optimal solution to the problem, meeting the development and batch production scheduling needs of the manufacturer.

[0066] The technical solution in the embodiment of the present application is to solve the above technical problems, and the overall idea is as follows:

[0067] The existing high-end equipment development and batch production optimization problem mainly considers the two-stage problem of self-development and batch production by the manufacturer, and fails to take the production outsourcing situation into consideration. Therefore, the scheduling results do not meet the requirements of actual manufacturing companies. At the same time, precise algorithms and simulation algorithms are often used to solve such problems, and the solution efficiency is low. In order to solve the above problems, an embodiment of the present invention proposes a high-end equipment development and batch production collaborative scheduling method based on the production outsourcing situation. Under the premise of adding an outsourcing company, an improved iterative greedy method is used to accurately and quickly solve the approximate optimal solution of the problem, thereby promoting the efficiency of high-end equipment manufacturers in development and batch production and maximizing the profits of manufacturers.

[0068] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0069] Embodiment 1:

[0070] like Figure 1 As shown, a method for coordinated scheduling of high-end equipment development and batch production based on production outsourcing includes:

[0071] S1. Obtain high-end equipment order information, manufacturer’s R&D team and production line data;

[0072] S2, using a three-segment coding rule based on the order layer-development layer-batch production layer to generate an initialization population including multiple initial solutions; wherein, by comparing the outsourcing income of the order with the self-development batch production income, an order allocation sequence of the order layer of the initial solution is generated;

[0073] S3. Perform a destructive operation on each initial solution, and obtain multiple new solutions by comparing the outsourcing revenue of the order with the revenue of self-developed batch production, and taking maximizing the total revenue of the manufacturer as the optimization goal;

[0074] S4, performing local search and update for the orders for batch production developed by the manufacturer in the new solution;

[0075] S5. Determine whether it is greater than the iteration termination temperature. If so, go to S4 and re-execute the local search and update operation until the conditions are met; otherwise, output the global optimal solution, decode and obtain the self-developed batch production order set and its corresponding development team and production line, and combine the high-end equipment order information to obtain the outsourced order set.

[0076] The embodiment of the present invention is aimed at the collaborative scheduling problem of the two stages of development and batch production of high-end equipment manufacturers, and increases the situation where manufacturers outsource orders, which meets the actual needs of the development of high-end equipment enterprises. In view of the situation where manufacturers develop and batch produce by themselves, the optimization goal is to maximize the overall profit of the manufacturer, obtain the set of self-development and batch production orders and their corresponding development teams and production lines, and determine the set of outsourced orders accordingly.

[0077] In addition, the improved iterative greedy algorithm is used to quickly and accurately obtain the approximate optimal solution to the problem. The solution can meet the production needs of high-end equipment manufacturers, improve the efficiency of high-end equipment research and development and batch production, and increase the total revenue of high-end equipment manufacturers.

[0078] First of all, it should be noted that the solution provided by the present invention takes into account the following constraints:

[0079] First, the outsourcing company is responsible for the development and batch production of outsourced orders. The outsourcing company’s production capacity is not limited and there is no overdue situation.

[0080] Second, there is a tight front-end-tight back constraint on orders for which manufacturers are responsible for developing and mass producing, and mass production can only be carried out after the development is completed.

[0081] Third, the R&D team cannot carry out R&D work for two orders at the same time, and the production line cannot carry out batch production work for two orders at the same time.

[0082] like Figure 2 As shown, Figure 2 Given the flowchart of the improved iterative greedy algorithm, we will then Figure 2 The following are the steps of the above solution:

[0083] Corresponding to step S1, firstly obtain the high-end equipment order information, the manufacturer's research and development team and production line data to set the input parameters of the iterative greedy algorithm, including at least:

[0084] Order index j = 1, 2, ..., n;

[0085] Research team index r = 1, 2, ..., s;

[0086] Production line index i = 1, 2, ..., m;

[0087] Order revenue j ;

[0088] Order outsourcing fee oc j ;

[0089] Order delivery time j ;

[0090] Development cost of development team r PC r ;

[0091] Manufacturer's production line batch cost PC i .

[0092] It is not difficult to understand that in addition to obtaining the above execution parameters, the embodiment of the present invention also requires the operation parameters of the iterative greedy algorithm to be set in advance by default, including the initial temperature T0, the annealing coefficient Termination temperature T f , destruction rate θ, number of neighborhood structure sets NS, and neighborhood set count initialization ω=0.

[0093] Corresponding to step S2, the three-segment coding rule based on the order layer-development layer-batch production layer is then used to generate an initialization population including multiple initial solutions. The order allocation sequence of the order layer of the initial solution is generated by comparing the outsourcing income of the order with the self-development batch production income.

[0094] The embodiment of the present invention innovatively proposes a three-segment coding rule based on the order layer-development layer-batch production layer to encode the scheduling plan. Among them, the first segment is the order layer code PS, which represents the order allocation sequence; the second segment is the development layer code RS, which represents the development team allocation sequence corresponding to the order; the third segment is the batch production layer code BS, which represents the production line allocation sequence corresponding to the order. That is, the three segments of code together constitute the initial solution x 0 , including:

[0095] The generation of initial solutions includes the generation of order allocation initial solutions, the generation of development phase initial solutions, and the generation of batch production phase initial solutions. Among them, the assignment of the development phase is based on the development team, and the assignment of the batch production phase is based on the production line. The initial solution is divided into three parts:

[0096] like Figure 3 As shown, the encoding length of the order layer is the number of orders n, x j = {0,1}, when the order is outsourced, the value is 0, otherwise it is 1. Each column of the development layer encodes the development team corresponding to the order, where y r ={0,1,2…s}, when y r = 0, indicating that the order is outsourced. Each column code at the batch production level indicates the production line to which the order is assigned, where z i ={0,1,2…m}, when z i = 0, indicating that the order is outsourced. Therefore, the initial solution can be expressed as x 0 ={x1,…,x j ,…,x n ; y1,…,y r ,…,y s ; z1,…,z i ,…,z m}.

[0097] On this basis, this step specifically includes:

[0098] S21. Based on the high-end equipment order information, generate order allocation sequences of order layers in sequence, and initialize the order index j=1 of the order allocation sequence.

[0099] S22. Calculate the outsourcing revenue NP of order j oj NP aj , calculated as follows:

[0100] NP oj =u j -oc j (1)

[0101] NP aj =u j -max {FT j -d j ,0}·yc j -PC r ·YT jr -PC i ·PT ij (2)

[0102] Among them, Max is the maximization function; FT j represents the completion time of order j from the manufacturer to batch production; yc j YT represents the penalty cost per unit for overdue order j; jr represents the development time of order j in development team r; PT ij Represents the batch production time of order j in production line i.

[0103] Note that max{FT j -d j ,0} can be regarded as the overdue time of order j, then max{FT j -d j ,0}·yc j It represents the possible overdue penalty cost for order j to be developed and mass-produced by the manufacturer.

[0104] S23. Comparison of outsourcing benefits NP oj and self-developed batch production yield NP aj The size of NP oj ≥NP aj , outsource order j; otherwise, the manufacturer develops and batches the order by itself and assigns it to the corresponding development team r and production line i.

[0105] S24, update the earliest start time min (CS jr), and the earliest start time of batch production at production line i min(BT ij ), calculated as follows:

[0106]

[0107] Among them, min is the minimization function; CS jr indicates the start time of order j in development team r; It represents the time required to develop the order that is scheduled before order j and is in charge of development team r.

[0108] BT ij represents the start time of order j in production line i; WT jr represents the completion time of order j in development team r; It indicates the time required to batch produce the order that is placed before order j and is handled by production line i.

[0109] S25, let j = j + 1, if j is less than or equal to the total number of orders n, then go to S22 to recalculate the outsourcing revenue NP of order j oj NP aj , until the conditions are met; otherwise, the population initialization is terminated.

[0110] Corresponding to step S3, each initial solution is then destroyed, and multiple new solutions are obtained by comparing the outsourcing revenue of the order with the self-developed batch production revenue, and maximizing the total revenue of the manufacturer as the optimization goal; specifically, the following are included:

[0111] S31, based on the initial solution x 0 The number of orders for self-developed batch production and the destruction rate θ, generate the corresponding number of position coordinates, remove the initial solution x 0 The orders at the corresponding positions in the , and their corresponding R&D teams and production lines, get an incomplete solution x ′ , and put the removed orders into the set of orders to be inserted δ;

[0112] S32, randomly select an order j from the set δ, remove it from the set and insert it into x ′ All possible positions in

[0113] S33, update the manufacturer's research and development batch production completion time of each order after order j is inserted, and recalculate the self-development batch production revenue NP of each order aj , if you develop and mass produce the profit NP aj Lower than outsourcing benefits NP oj , the order will be outsourced;

[0114] S34, calculating the total revenue TP of manufacturers at different insertion positions, and selecting the solution with the largest total revenue TP of manufacturers as the insertion solution for order j; wherein the total revenue TP of manufacturers is calculated as follows:

[0115]

[0116] Among them, X j is a decision variable used to distinguish whether order j is developed and mass-produced by the manufacturer itself.

[0117] S35. Determine whether the set δ is an empty set. If not, go to S32 and select a new order j from the set δ. ′ Perform the insertion operation until the condition is met; if so, end the reconstruction operation and output the new solution x 1 .

[0118] Corresponding to step S4, a local search and update is performed on the orders for batch production developed by the manufacturer in the new solution.

[0119] like Figure 2 As shown, in this step, the following are specifically performed:

[0120] For the new solution x 1 The manufacturer develops batch production orders and performs local search and update to obtain the local optimal solution x 2 , a relatively new solution x 1 The fitness and local optimal solution x 2 The fitness value of 2 The fitness value is less than x 1 The fitness value of x 1 =x 2 , continue the local search in the current neighborhood structure; if x 2 The fitness value is not less than x 1 fitness value, let ω=ω+1, and determine whether ω≤NS holds. If so, repeat the local search and update operation in this step; otherwise, go to S5.

[0121] Exemplarily, the above fitness function can directly use the total profit TP calculation formula given by formula (5).

[0122] In addition, the embodiments of the present invention also design the following multiple neighborhood structures to perform local search update operations:

[0123] Neighborhood structure 1: Define variable h1, randomly generate an integer in the interval [1,n] and assign it to h1. For the order allocation sequence PS of the order layer, determine whether the orders at the h1th position and the 1st position are both developed and mass-produced by the manufacturer. If so, swap the order codes at the h1th position and the 1st position, otherwise leave them unchanged.

[0124] Neighborhood Structure 2: Define variables h1 and h2, randomly generate two integers in the interval [1, n], assign them to h1 and h2 such that h1 < h2. For the research team assignment sequence RS in the research layer, determine whether the orders at the h1-th position and the h2-th position are both for manufacturer research. If so, swap the order codes at the h1-th position and the h2-th position; otherwise, do not change.

[0125] Neighborhood Structure 3: Define variables h1 and h2, randomly generate two integers in the interval [1, n], assign them to h1 and h2 such that h1 < h2. For the production line assignment sequence BS in the mass production layer, swap the order codes of the orders responsible for mass production by the manufacturer on the left side of the h1-th position and on the right side of the h2-th position.

[0126] Neighborhood Structure 4: Define variables h1, h2, and h3, randomly generate three integers in the interval [1, b], assign them to h1, h2, and h3 such that h1 < h2 < h3. For the research team assignment sequence RS in the research layer, reverse the order codes of the orders responsible for mass production by the manufacturer on the left side of the h1-th position and on the right side of the h3-th position. For the production line assignment sequence BS in the mass production stage, reverse the order codes of the orders responsible for mass production by the manufacturer between the h1-th position and the h2-th position.

[0127] Corresponding to step S5, finally determine whether it is greater than the iteration termination temperature. If so, transfer to S4 to re-execute the local search update operation until the condition is satisfied; otherwise, output the global optimal solution, decode to obtain the set of self-developed mass production orders and their corresponding research teams and production lines, and combine the high-end equipment order information to obtain the set of outsourced orders.

[0128] As Figure 2 shown, in this step, specifically calculate the current temperature T, where and determine whether the current temperature T is greater than the iteration termination temperature T f , if so, return to S3; otherwise, output the global optimal solution x best , and for the global optimal solution x best perform decoding to end the algorithm.

[0129] Corresponding to the encoding rule, the embodiment of the present invention designs the following decoding rule:

[0130] For the research team assignment sequence in the research layer, obtain the orders assigned to each research team. When multiple orders are assigned to research team r, compare the research times YT of different orders j in this research team r jr , select the order j with a longer research time to be developed first. If the order research times are the same, then preferentially select the order j with a higher income u j to be developed;

[0131] For the production line allocation sequence of the batch production layer, obtain the orders assigned to each production line; when multiple orders are assigned to production line i, compare the earliest completion time min (WT jr ), select the order j with the earliest development completion time for batch production. If the development completion time of the orders is the same, the order with revenue u is preferred. j Higher order j for batch production;

[0132] Combining the decoding results of the two parts, we can obtain the self-developed batch production order set and the corresponding development team and production line.

[0133] Thus, this step can obtain the self-developed batch production order set and its corresponding development team and production line, and combine the original high-end equipment order information, that is, the total order set, and can also obtain the outsourced order set. So far, the embodiment of the present invention completes the entire process of the high-end equipment development and batch production collaborative scheduling method based on production outsourcing.

[0134] Embodiment 2:

[0135] The embodiment of the present invention provides a high-end equipment development and batch production collaborative scheduling system based on production outsourcing, including:

[0136] The acquisition module is used to obtain high-end equipment order information, manufacturer's research and development team and production line data;

[0137] An initialization module is used to generate an initialization population including a plurality of initial solutions by adopting a three-segment coding rule based on the order layer, the research layer and the batch production layer; wherein the order allocation sequence of the order layer of the initial solution is generated by comparing the outsourcing income of the order with the self-research and batch production income;

[0138] The comparison module is used to destroy each initial solution, and obtain multiple new solutions by comparing the outsourcing revenue of the order with the revenue of self-developed batch production, and taking maximizing the total revenue of the manufacturer as the optimization goal;

[0139] An updating module, used for performing local search and update on the orders for batch production of the manufacturer in the new solution;

[0140] The output module is used to determine whether it is greater than the iteration termination temperature. If so, the local search and update operation is re-executed until the conditions are met; otherwise, the global optimal solution is output, the self-developed batch production order set and its corresponding development team and production line are decoded, and the outsourced order set is obtained in combination with the high-end equipment order information.

[0141] Embodiment 3:

[0142] An embodiment of the present invention provides a storage medium storing a computer program for coordinated scheduling of high-end equipment development and batch production based on production outsourcing, wherein the computer program enables a computer to execute the method for coordinated scheduling of high-end equipment development and batch production as described in Example 1.

[0143] Embodiment 4:

[0144] An embodiment of the present invention provides an electronic device, including:

[0145] One or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the programs include a method for executing the high-end equipment development and batch production coordinated scheduling method as described in Example 1.

[0146] It can be understood that the high-end equipment development and batch production collaborative scheduling system based on production outsourcing, storage medium and electronic device provided in the embodiments of the present invention correspond to the high-end equipment development and batch production collaborative scheduling method based on production outsourcing provided in the embodiments of the present invention, and the explanations, examples and beneficial effects of the relevant contents can refer to the corresponding parts in the high-end equipment development and batch production collaborative scheduling method, which will not be repeated here.

[0147] In summary, compared with the prior art, the present invention has the following beneficial effects:

[0148] 1. The embodiment of the present invention coordinates the two stages of development and batch production of high-end equipment manufacturers, and comprehensively considers the development, batch production and overdue costs in the setting of the fitness function, so that the scheduling result meets the global optimum.

[0149] 2. The implementation of the present invention focuses on the situation where manufacturers outsource the production of orders, so that the solution analysis conforms to the actual situation and can better guide the research and development and batch production work of high-end equipment manufacturers.

[0150] 3. The present invention improves the iterative greedy algorithm and uses a more efficient initialization method when seeking the initial solution, which speeds up the algorithm iteration speed. In the destruction stage, a new destruction method is designed in combination with the destruction rate to increase the diversity of solutions and expand the search range of the algorithm.

[0151] 4. The example of the present invention designs four neighborhood structures according to the actual problem background, including changes in the order allocation method and adjustments and changes in the corresponding development team and production line sequence, which can improve the quality of the solution while meeting the problem constraints, thereby improving the algorithm's ability to search for the global optimal solution.

[0152] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0153] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. 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 embodiments of the present invention.

Claims

1. A method for coordinated scheduling of high-end equipment development and batch production based on production outsourcing, characterized in that: include: Obtain high-end equipment order information, manufacturer's R&D team and production line data; An initialization population including a plurality of initial solutions is generated by adopting a three-segment coding rule based on the order layer, the research layer and the batch production layer; wherein, the order allocation sequence of the order layer of the initial solution is generated by comparing the outsourcing income of the order with the self-research batch production income; Destroy each initial solution, compare the outsourcing revenue of the order with the revenue of self-developed batch production, and take maximizing the total revenue of the manufacturer as the optimization goal to obtain multiple new solutions; Performing a local search and update on the orders for batch production by the manufacturer in the new solution; Determine whether it is greater than the iteration termination temperature. If so, re-execute the local search and update operation until the condition is met; otherwise, output the global optimal solution, decode and obtain the self-developed batch production order set and its corresponding development team and production line, and combine the high-end equipment order information to obtain the outsourced order set.

2. The high-end equipment development and batch production coordinated scheduling method according to claim 1 is characterized in that: The method adopts a three-stage coding rule based on the order layer, the research layer and the batch production layer to generate an initialization population including multiple initial solutions; including: Based on the high-end equipment order information, an order allocation sequence of the order layer is generated in sequence, and the order index j=1 of the order allocation sequence is initialized; Calculate the outsourcing revenue NPo of order j j NP aj ; Compare Outsourcing BenefitsNP oj and self-developed batch production yield NP aj The size of NP oj ≥NP aj , outsource order j; otherwise, the manufacturer develops and batches it by itself and assigns it to the corresponding development team r and production line i; Update the earliest start time min (CS jr ), and the earliest start time of batch production at production line i min(BT ij ); Let j = j + 1. If j is less than or equal to the total number of orders n, then recalculate the outsourcing revenue NP of order j. oj NP aj , until the conditions are met; otherwise, the population initialization is terminated.

3. The high-end equipment development and batch production coordinated scheduling method according to claim 2 is characterized in that: Outsourcing revenue NP for order j oj NP aj The calculation method is as follows: NP oj =u j -oc j (1) NP aj =u j -max{FT j -d j ,0}·yc j -PC r ·YT jr -PC i ·PT ij (2) Among them, u j represents the revenue of order j; oc j represents the outsourcing cost of order j; Max is the maximization function; FT j represents the completion time of order j from the manufacturer to batch production; d j represents the delivery date of order j; yc j represents the overdue penalty cost per unit for order j; PC r represents the development cost of development team r; YT jr represents the development time of order j in development team r; PC i Batch production cost of production line i; PT ij Represents the batch production time of order j in production line i.

4. The high-end equipment development and batch production coordinated scheduling method according to claim 2 is characterized in that: The earliest start time for order j to be developed by development team r is min(CS jr ) and the earliest start time of batch production at production line i min(BT ij ) is calculated as follows: Among them, min is the minimization function; CS jr indicates the start time of order j in development team r; It indicates the time required to develop the order that is in the order queue and is in charge of by the development team r; BT ij represents the start time of order j in production line i; WT jr represents the completion time of order j in development team r; It indicates the time required to batch produce the order that is placed before order j and is handled by production line i.

5. The high-end equipment development and batch production coordinated scheduling method according to claim 3 is characterized in that: The destruction operation is performed on each initial solution, and multiple new solutions are obtained by comparing the outsourcing revenue of the order with the revenue of self-developed batch production, and maximizing the total revenue of the manufacturer as the optimization goal; including: Based on the initial solution x 0 The number of orders for self-developed batch production and the destruction rate θ, generate the corresponding number of position coordinates, remove the initial solution x 0 The orders at the corresponding positions in the , their corresponding R&D teams and production lines, are used to obtain the incomplete solution x′, and the removed orders are placed in the set of orders to be inserted δ; Randomly select an order j from the set δ, remove it from the set and insert it into all possible positions in x′; Update the manufacturer's development and batch production completion time for each order after order j is inserted, and recalculate the self-development and batch production revenue NP for each order aj If you develop and mass produce the profit NP aj Lower than outsourcing benefits NP oj , the order will be outsourced; Calculate the total revenue TP of manufacturers at different insertion positions, and select the solution with the largest total revenue TP of manufacturers as the order and insertion solution; the calculation method of the total revenue TP of manufacturers is as follows: Among them, s is the total number of research and development teams; m is the total number of production lines; X j is the decision variable; Determine whether the set δ is an empty set. If not, select a new order j′ from the set δ for insertion until the condition is met. If so, end the reconstruction operation and output the new solution x 1 .

6. The high-end equipment development and batch production coordinated scheduling method according to claim 2 is characterized in that: The following various neighborhood structures are designed to perform local search update operations: Neighborhood structure 1: define variable h1, randomly generate an integer in the interval [1, n] and assign it to h1. For the order allocation sequence PS of the order layer, determine whether the orders at the h1th position and the 1st position are both developed and batch produced by the manufacturer. If so, swap the order codes at the h1th position and the 1st position, otherwise, do not change; Neighborhood structure 2: define variables h1 and h2, randomly generate two integers in the interval [1, n], assign them to h1 and h2, so that h1 < h2, assign sequence RS to the development team at the development layer, and determine whether the orders at the h1th position and the h2th position are both developed by the manufacturer. If so, swap the order codes at the h1th position and the h2th position, otherwise, do not change; Neighborhood structure 3: Define variables h1 and h2, randomly generate two integers in the interval [1, n], assign them to h1 and h2, so that h1 < h2, allocate sequence BS to the production line of the batch production layer, and swap the order codes of the manufacturer responsible for batch production on the left side of the h1th position and the right side of the h2th position; Neighborhood structure 4: define variables h1, h2, and h3, randomly generate three integers in the interval [1, n], and assign them to h1, h2, and h3, so that h1<h2<h3; allocate sequence RS to the development team at the development layer, and reverse the order codes of the manufacturer responsible for batch production on the left side of the h1th position and on the right side of the h3th position; allocate sequence BS to the production line in the batch production stage, and reverse the order codes of the manufacturer responsible for batch production between the h1th position and the h2th position.

7. The high-end equipment development and batch production coordinated scheduling method according to claim 1 is characterized in that: The decoding rules include: For the development team allocation sequence of the development layer, obtain the orders assigned to each development team; when multiple orders are assigned to development team r, compare the development time YT of different orders j in this development team r jr , select the order j with the longest development time for development first, if the order development time is the same, then the income u is preferred j Higher order j for development; For the production line allocation sequence of the batch production layer, obtain the orders assigned to each production line; when multiple orders are assigned to production line i, compare the earliest completion time min (WT jr ), select the order j with the earliest development completion time for batch production. If the development completion time of the orders is the same, the order with revenue u is preferred. j Higher order j for batch production; Combining the decoding results of the two parts, we can obtain the self-developed batch production order set and the corresponding development team and production line.

8. A high-end equipment development and batch production collaborative scheduling system based on production outsourcing, characterized in that: include: The acquisition module is used to obtain high-end equipment order information, manufacturer's research and development team and production line data; An initialization module is used to generate an initialization population including a plurality of initial solutions by adopting a three-segment coding rule based on the order layer, the research layer and the batch production layer; wherein the order allocation sequence of the order layer of the initial solution is generated by comparing the outsourcing income of the order with the self-research and batch production income; The comparison module is used to destroy each initial solution, and obtain multiple new solutions by comparing the outsourcing revenue of the order with the revenue of self-developed batch production, and taking maximizing the total revenue of the manufacturer as the optimization goal; An updating module, used for performing local search and update on the orders for batch production of the manufacturer in the new solution; The output module is used to determine whether it is greater than the iteration termination temperature. If so, the local search and update operation is re-executed until the conditions are met; otherwise, the global optimal solution is output, the self-developed batch production order set and its corresponding development team and production line are decoded, and the outsourced order set is obtained in combination with the high-end equipment order information.

9. A storage medium, characterized in that: It stores a computer program for coordinated scheduling of high-end equipment development and batch production based on production outsourcing, wherein the computer program enables the computer to execute the method for coordinated scheduling of high-end equipment development and batch production as described in any one of claims 1 to 7.

10. An electronic device, characterized in that: include: one or more processors; Memory; And one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the programs include programs for executing the high-end equipment development and batch production collaborative scheduling method as described in any one of claims 1 to 7.

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