A method for manufacturing task service resource allocation, a storage medium, and an apparatus

Abstract

The application discloses a manufacturing task service resource allocation method, a storage medium and equipment, and the method comprises the following steps: constructing a service resource allocation model by taking the minimum weighted value of the total time cost and the total fund cost of a manufacturing task in multiple service stages as the target and combining constraint conditions; and determining the optimal service resource allocation scheme of the manufacturing task by using a genetic algorithm based on the service resource allocation model, so that the optimal scheme of the manufacturing task service resource allocation can be quickly and effectively determined.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of resource allocation of manufacturing tasks, and particularly relates to a manufacturing task service resource allocation method, a storage medium and equipment. BACKGROUND

[0002] Domestic manufacturing enterprises face overseas procurement orders, which need to call domestic procurement, production and other services to produce and process products, and transport all orders through the logistics network to foreign countries through ports and shipping companies. This process includes procurement, production and processing, warehousing, transportation and other links. Allocating appropriate resources for manufacturing tasks in different links is beneficial to improve the supply efficiency and cost of products.

[0003] At present, resource allocation is mainly completed by manual calculation in the market. However, manufacturing task service resource allocation has characteristics such as manufacturing task service resource heterogeneity and manufacturing task service resource network complexity. Only relying on manual experience, it is difficult to determine the optimal resource allocation scheme from the overall perspective, and there are problems such as low resource allocation efficiency and unreasonable allocation. SUMMARY

[0004] The technical problem to be solved by the present application is how to quickly and effectively determine the optimal scheme of manufacturing task service resource allocation.

[0005] To solve the above technical problems, the present application provides a manufacturing task service resource allocation method, a storage medium and equipment.

[0006] In a first aspect, the present application provides a manufacturing task service resource allocation method, which comprises:

[0007] A service resource allocation model is constructed with the minimum weighted value of total time cost and total fund cost of manufacturing tasks in multiple service stages as the target and in combination with constraint conditions;

[0008] Based on the service resource allocation model, a genetic algorithm is used to determine the optimal service resource allocation scheme of the manufacturing task.

[0009] In some embodiments, based on the service resource allocation model, a genetic algorithm is used to determine the optimal service resource allocation scheme of the manufacturing task, which comprises:

[0010] Step S201: An initial population is constructed based on the time cost and fund cost of the manufacturing task in each service stage;

[0011] Step S202: The fitness of the initial population is calculated according to the objective function;

[0012] Step S203: judging whether the iteration is terminated, if the iteration is terminated, executing step S206; otherwise, proceeding to step S204;

[0013] Step S204: performing genetic operation on the initial population to obtain a child population;

[0014] Step S205: calculating the fitness of the child population according to the objective function;

[0015] Step S206: outputting the optimal solution of the service resource allocation model when all the populations are iterated to be terminated.

[0016] In some embodiments, the constructing the service resource allocation model with the objective of minimizing the weighted value of total time cost and total capital cost of the manufacturing task in multiple service stages and combining constraint conditions comprises:

[0017] constructing an objective function with the objective of minimizing the weighted value of total time cost and total capital cost of the manufacturing task in multiple service stages:

[0018] min F = ω1T + ω2C

[0019] wherein, F is the objective function, T is the total time cost in multiple service stages, C is the total capital cost in multiple service stages, ω1 is the weight factor of the total time cost, and ω2 is the weight factor of the total capital cost;

[0020] the constraint conditions comprise a total time cost constraint condition and a total capital cost constraint condition, and the total time cost constraint condition is expressed as:

[0021] T ≤ T max , wherein T max is a preset threshold of total time cost in multiple service stages;

[0022] the total capital cost constraint condition is expressed as:

[0023] C ≤ C max , wherein C max is a preset threshold of total capital cost in multiple service stages.

[0024] In some embodiments, the constraint conditions further comprise a time coordination constraint condition and / or a region coordination constraint condition.

[0025] In some embodiments, the service stages comprise a supplier service stage, a production service stage, a warehouse service stage, a large ship service stage, and a small ship service stage.

[0026] In some embodiments, the time cost of the supplier service stage includes the material procurement time of the supplier; the capital cost of the supplier service stage includes the material procurement cost of the supplier;

[0027] The time cost of the production service stage includes the waiting time and service time at the production base; the capital cost of the production service stage includes the production cost at the production base;

[0028] The time cost of the warehousing service stage includes the material storage time and the finished product storage time in the warehouse; the capital cost of the warehousing service stage includes the material storage cost and the finished product storage cost in the warehouse;

[0029] The time cost of the vessel service phase includes the time the vessel is in port; the capital cost of the vessel service phase includes the booking cost of the vessel and the transportation cost from the warehouse to the port where the vessel is located;

[0030] The time cost of the boat service stage includes the time the boat is in the port; the capital cost of the boat service stage includes the booking cost of the boat and the transportation cost from the warehouse to the port where the boat is located.

[0031] In some embodiments, the time coordination constraints include:

[0032] TS=t u

[0033]

[0034] Where TS represents the temporal synergy strength; t u Indicates meaningless time; i represents the number of the manufacturing task, i = 1, 2..., I; Indicates the production start time of the production base, Indicates the supplier's procurement arrival time, Indicates the start time of material procurement at the supplier. Indicates the production end time of the production base, Indicates the actual departure time of the large ship at the port, Indicates the time when large ships start operations in the port.

[0035] In some embodiments, the regional coordination constraints include:

[0036]

[0037]

[0038] Wherein, RS represents the regional coordination strength of the production base and the warehouse; i represents the number of manufacturing tasks, i=1, 2, …, I; G is a positive number.

[0039] In a second aspect, the application provides a storage medium, wherein the storage medium stores a computer program, and the computer program is executed by a processor to implement the manufacturing task service resource allocation method.

[0040] In a third aspect, the application provides a device, which comprises a memory and a processor, and the memory stores a computer program, and the computer program is executed by the processor to implement the manufacturing task service resource allocation method.

[0041] Compared with the prior art, one or more embodiments of the above scheme can have the following advantages or beneficial effects:

[0042] By applying the manufacturing task service resource allocation method provided by the application, the service resource allocation model is constructed by taking the minimum weighted value of the total time cost and the total fund cost of the manufacturing task in multiple service stages as the target and combining the constraint conditions; and the optimal service resource allocation scheme of the manufacturing task is determined by using the genetic algorithm based on the service resource allocation model, so that the optimal scheme of the manufacturing task service resource allocation can be quickly and effectively determined. BRIEF DESCRIPTION OF DRAWINGS

[0043] The scope of the present disclosure can be better understood by reading the following detailed description of exemplary embodiments in conjunction with the accompanying drawings, which are included as a part of this disclosure. The drawings are:

[0044] Figure 1 A flowchart of a manufacturing task service resource allocation method provided by an embodiment of the application is shown;

[0045] Figure 2 A flowchart of a method for determining the optimal service resource allocation scheme of a manufacturing task by using a genetic algorithm provided by an embodiment of the application is shown;

[0046] Figure 3 A structural diagram of a device provided by an embodiment of the application is shown. DETAILED DESCRIPTION

[0047] In order to make the purpose, technical scheme and advantages of the application clearer, the implementation method of the application will be described in detail below in conjunction with the drawings and embodiments, so that the implementation process of how the application applies technical means to solve technical problems and achieve technical effects can be fully understood and implemented.

[0048] Domestic manufacturing enterprises face overseas procurement orders, need to call domestic procurement, production and other services to produce and process products, and through the port and shipping company to transport all orders through the logistics network to foreign countries. This process includes procurement, production and processing, warehousing, transfer and other links, and allocating appropriate resources for different manufacturing tasks is beneficial to improve the supply efficiency and cost of products.

[0049] At present, the resource allocation is mainly completed by manual calculation in the market, however, the manufacturing task service resource allocation has the characteristics of manufacturing task service resource heterogeneity and manufacturing task service resource network complexity, only relying on manual experience, it is difficult to determine the optimal resource allocation scheme from the overall perspective, and there are problems of low resource allocation efficiency and unreasonable allocation.

[0050] The manufacturing task service resource allocation method provided by the application takes the minimum weighted value of the total time cost and the total fund cost of the manufacturing task in multiple service stages as the target and combines the constraint conditions to construct a service resource allocation model; based on the service resource allocation model, the genetic algorithm is used to determine the optimal service resource allocation scheme of the manufacturing task. The method considers the service resources involved in each service stage, achieves the purpose of comprehensive overall optimization of resource allocation, reduces the phenomenon of resource idling or resource shortage, can quickly and effectively determine the optimal scheme of manufacturing task service resource allocation, makes the service resources be reasonably allocated, and improves the efficiency of the overall process of manufacturing task service resource allocation.

[0051] Example One

[0052] Referring to Figure 1 , Figure 1 A flowchart of a manufacturing task service resource allocation method provided by an embodiment of the application is shown, which can include:

[0053] Step S101: taking the minimum weighted value of the total time cost and the total fund cost of the manufacturing task in multiple service stages as the target and combining the constraint conditions, constructing a service resource allocation model;

[0054] Step S102: based on the service resource allocation model, using the genetic algorithm to determine the optimal service resource allocation scheme of the manufacturing task.

[0055] In some embodiments, step S101 can be specifically: taking the minimum weighted value of the total time cost and the total fund cost of the manufacturing task in multiple service stages, constructing an objective function:

[0056] minF=ω1T+ω2C

[0057] wherein F is the objective function, T is the total time cost over the plurality of service stages, C is the total capital cost over the plurality of service stages, ω1 is a weight factor for the total time cost, and ω2 is a weight factor for the total capital cost;

[0058] The constraints include a total time cost constraint and a total capital cost constraint. The total time cost constraint is expressed as:

[0059] T≤T max , wherein T max is a pre-set threshold for the total time cost over the plurality of service stages;

[0060] The total capital cost constraint is expressed as:

[0061] C≤C max , wherein C max is a pre-set threshold for the total capital cost over the plurality of service stages.

[0062] In some embodiments, the service stages can include a supplier service stage, a production service stage, a warehousing service stage, a large ship service stage, and a small ship service stage. The complete supply chain related to the manufacturing task is involved, which is conducive to the overall optimization of the allocation of service resources.

[0063] The total time cost can be expressed as:

[0064] T=T P +T M +T S +T V +T B

[0065] wherein T P represents the time cost of the supplier service stage, T M represents the time cost of the production service stage, T S represents the time cost of the warehousing service stage, T V represents the time cost of the large ship service stage, and T B represents the time cost of the small ship service stage.

[0066] The total capital cost can be expressed as:

[0067] C=C P +C M +C S +C V +C B

[0068] wherein C P represents the capital cost of the supplier service stage, C M represents the capital cost of the production service stage, C SC represents the capital cost of the warehouse service stage, V C represents the capital cost of the large ship service stage, B C represents the capital cost of the small ship service stage.

[0069] In some embodiments, the time cost T P of the supplier service stage can include the material procurement time of the supplier; the capital cost C P of the supplier service stage can include the material procurement cost of the supplier; wherein the material procurement time can be represented as:

[0070]

[0071] i represents the number of manufacturing tasks, i = 1, 2, …, I; j represents the number of atomic manufacturing tasks under each manufacturing task; k represents the service number of the atomic manufacturing task; Tk represents the material procurement start time of the k ij th supplier, Tk represents the material procurement arrival time of the k ij th supplier, Xk is a decision variable, taking 1 means choosing the k ij th supplier, and taking 0 means not choosing the k ij th supplier;

[0072] The material procurement cost can be represented as:

[0073]

[0074] Tk represents the unit material procurement cost of the k ij th supplier, Tk represents the material procurement quantity of the k ij th supplier.

[0075] In some embodiments, the time cost T M of the production service stage can include the waiting time and service time of the production base; the capital cost C M of the production service stage can include the production cost of the production base; wherein the time cost of the production service stage can be represented as:

[0076]

[0077] Tk represents the waiting time of the k ij th production base, such as the time required for production and processing parts; Tk represents the service time of the k ij th production base, such as the time for communicating with customers about parts; is a decision variable, taking 1 to indicate the selection of the kth ij production bases, and 0 means not selecting the kth production base. ij production bases;

[0078] The production cost of a production base can be expressed as:

[0079]

[0080] Indicates that the kth ij Unit production costs of each production base; Indicates that the kth ij The production quantity of each production base.

[0081] In some embodiments, the time cost T of the warehousing service stage is S Including the material storage time and finished product storage time in the warehouse; the capital cost C of the warehousing service stage S Including the material storage cost and finished product storage cost in the warehouse; Among them, the time cost of the warehousing service stage is T S It can be expressed as:

[0082]

[0083]

[0084]

[0085] T SM (k ij ) indicates that the kth ij Material storage time in a warehouse, Indicates that the kth ij The production start time of each production base, Indicates the kth ij The procurement arrival time of suppliers; T SP (k ij ) indicates that the kth ij Finished product storage time in each warehouse, Indicates the time when the large ship starts operating in the port. Indicates that the kth ij The production completion time of each production base; is a decision variable, taking 1 to indicate the selection of the kth ij warehouses, 0 means not to select the kth warehouse ij warehouses;

[0086] The material storage cost can be the product of the material storage space, unit material storage cost and material storage time. The finished product storage cost can be the product of the finished product storage space, unit finished product storage cost and finished product storage time. The capital cost C of the warehousing service stage is S It can be expressed as:

[0087]

[0088] Indicates that the kth ij Material storage space in a warehouse, Indicates that the kth ij Finished product storage space in a warehouse, Indicates the kth ij The unit material storage cost of a warehouse, Indicates the kth ij The unit finished product storage cost of a warehouse.

[0089] In some embodiments, the time cost of the large ship service stage is T V Including the time the vessel is in port; the capital cost C during the vessel service phase V This includes the vessel booking cost and the transportation cost from the warehouse to the port where the vessel is located. The vessel's time in port can be expressed as:

[0090]

[0091] Indicates the actual departure time of the ship. Indicates the time when the large ship starts operating in the port. is a decision variable, taking 1 to indicate the selection of the kth ij The long-distance ship service in the time period, 0 means not to select the kth time ij Long-distance ship services during the time period;

[0092] Capital cost C during the large ship service phase V It can be expressed as:

[0093]

[0094]

[0095]

[0096] C VT (k ij ) represents the transportation cost from the warehouse to the port where the ship is located, C VB (k ij ) represents the booking cost of the large vessel; the transportation cost from the warehouse to the port where the large vessel is located, C VT (k ij) can be the unit distance transportation cost c from the warehouse to the port where the ship is located VT The product of the Euclidean distance d from the warehouse to the port where the ship is located; the booking cost of the ship C VB (k ij ) can be the kth ij Large vessel position price during the time period With the kth ij Number of large vessel positions in the time period The product of .

[0097] In some embodiments, the time cost T of the boat service phase B Including the time the boat is in port; the capital cost of the boat service phase C B This includes the booking cost of the boat and the transportation cost from the warehouse to the port where the boat is located. The time the boat is in port can be expressed as:

[0098]

[0099] Indicates the actual departure time of the boat. Indicates the time when the boat starts operating in the port. is a decision variable, taking 1 to indicate the selection of the kth ij The boat service in the time period, 0 means not to select the kth time period ij Small boat service during time periods;

[0100] Capital cost of the boat service phase C B It can be expressed as:

[0101]

[0102]

[0103]

[0104] C BT (k ij ) represents the transportation cost from the warehouse to the port where the boat is located, C BB (k ij ) represents the booking cost of the boat; the transportation cost from the warehouse to the port where the boat is located, C BT (k ij ) can be the unit distance transportation cost c from the warehouse to the port where the boat is located BT The product of the Euclidean distance d' from the warehouse to the port where the boat is located; the booking cost of the boat C BB (k ij ) can be the kth ij Small boat position price for the time period With the kth ijThe number of small-boat positions for a time period The product of the number of small-boat positions for a time period and the time period.

[0105] In some embodiments, referring to FIG. 1, a manufacturing task is shown, and the manufacturing task includes a plurality of service stages, and each service stage includes a plurality of time periods. Figure 2 Figure 2 FIG. 2 shows a flowchart of a method for determining an optimal service resource allocation scheme for a manufacturing task using a genetic algorithm according to an embodiment of the present application. Step S102 can specifically include:

[0106] Step S201: constructing an initial population based on the time cost and the fund cost of the manufacturing task in each service stage;

[0107] Step S202: calculating the fitness of the initial population according to the objective function;

[0108] Step S203: determining whether the iteration is terminated, if the iteration is terminated, executing step S206; otherwise, executing step S204;

[0109] Step S204: performing genetic operations on the initial population to obtain a child population;

[0110] Step S205: calculating the fitness of the child population according to the objective function;

[0111] Step S206: outputting the optimal solution of the service resource allocation model when all populations are iterated to be terminated.

[0112] In some embodiments, step S203 can specifically include determining whether the iteration is terminated according to a preset index, and when the iteration is terminated, the optimal solution of the service resource allocation model can be outputted, that is, the optimal service resource allocation scheme for the manufacturing task can be obtained. Each chromosome corresponds to a solution, and taking the service stages including the supplier service stage, the production service stage, the warehouse service stage, the large-boat service stage, and the small-boat service stage as an example, the optimal solution can be obtained to determine the time cost and the fund cost of the manufacturing task allocated in each service stage, and further to determine the selected suppliers, production bases, warehouses, large boats corresponding to time periods, and small boats corresponding to time periods.

[0113] In some embodiments, the genetic operations can include selection operations, crossover operations, and mutation operations, the selection operations can be based on the fitness of each individual in the obtained population to select a plurality of individuals with greater fitness to copy to the next generation, and the child population can be obtained through the selection operations, the crossover operations, and the mutation operations.

[0114] In some embodiments, the constraint conditions can further include time coordination constraint conditions and / or regional coordination constraint conditions to further improve the rationality of the service resource allocation.

[0115] In some embodiments, the time coordination constraint conditions can include: ​

[0116] TS = t u

[0117]

[0118] wherein, TS represents time coordination strength; t u represents meaningless time; i represents the number of manufacturing tasks, i = 1, 2, …, I; represents the production start time of the production base, represents the purchase arrival time of the supplier, represents the material purchase arrival time of the supplier, represents the production end time of the production base, represents the actual departure time of the large ship, represents the time when the large ship starts work in the port.

[0119] In some embodiments, the regional coordination constraint condition can include:

[0120]

[0121]

[0122] wherein, RS represents the regional coordination strength between the production base and the warehouse; i represents the number of manufacturing tasks, i = 1, 2, …, I; G is a positive number.

[0123] wherein, G can be selected as a large positive number according to specific needs.

[0124] As a specific example, when 100,000 air conditioners need to be ordered overseas, assuming that there are ten domestic suppliers to choose from, the total capital cost and total time cost of the ten suppliers can be determined respectively according to the known regional coordination constraint condition and time coordination constraint condition, and the cost parameters and time parameters of each supplier and the related service stage are brought in by combining the genetic algorithm, for example, because the geographical positions of the suppliers and the shipping ports are different, the transportation cost and time caused by the selection and allocation of small ships and large ships will also be different, at this time the genetic algorithm can continuously calculate different permutations and combinations of known conditions, and then determine the optimal service resource allocation scheme from them.

[0125] The above is a manufacturing task service resource allocation method provided by the embodiment of the application, which constructs a service resource allocation model by taking the weighted value of the total time cost and the total capital cost of the manufacturing task in multiple service stages as the target and combining the constraint conditions; based on the service resource allocation model, the genetic algorithm is used to determine the optimal service resource allocation scheme of the manufacturing task, so that the optimal scheme of the manufacturing task service resource allocation can be quickly and effectively determined.

[0126] Example Two

[0127] Another aspect of the present application also provides a storage medium, wherein a computer program is stored, and the computer program is executable by a processor to implement the manufacturing task service resource allocation method in the above embodiment one.

[0128] The processes, functions, methods and / or software described above can be recorded, stored or fixed in one or more computer readable storage media, including program instructions to be implemented by a computer to cause a processor to execute the program instructions. The storage medium can also include program instructions, data files, data structures, etc. alone or in combination. The storage medium or program instructions can be specifically designed and understood by those skilled in the computer software field, or the storage medium or instructions can be known and available to those skilled in the computer software field. Examples of computer readable media include magnetic media, such as hard disks, floppy disks and magnetic tapes; optical media, such as CD ROM disks and DVDs; magneto-optical media, such as optical disks; and hardware devices specifically configured to store and execute program instructions, such as read-only memory (ROM), random access memory (RAM), flash memory, etc. Examples of program instructions include machine code (e.g. code generated by a compiler) and files containing high-level code that can be executed by a computer by using an interpreter. The described hardware devices can be configured to function as one or more software modules to perform the above-described operations and methods, and vice versa. In addition, the computer readable storage medium can be distributed in a networked computer system, and the computer readable code or program instructions can be stored and executed in a distributed manner.

[0129] The computer program stored in the storage medium is executable by a processor to achieve the same beneficial effects as in embodiment one.

[0130] Example Three

[0131] Another aspect of the present application provides a device, referring to Figure 3 as shown, Figure 3 A device structure schematic diagram provided by an embodiment of the present application is shown, which includes a memory 31 and a processor 32, and the memory 31 stores a computer program, and the computer program is executable by the processor 32 to implement the manufacturing task service resource allocation method in the above embodiment one.

[0132] It should be noted that the device can include one or more processors 32 and a memory 31, which can be connected through a bus or other means. The memory 31, as a kind of non-volatile computer readable storage medium, can be used to store non-volatile software programs, non-volatile computer executable programs and modules. The processor 32 executes various functions of the device and data processing by running the non-volatile software programs, instructions and modules stored in the memory 31, that is, implements the manufacturing task service resource allocation method as described above.

[0133] Although the embodiments disclosed by the present application are as above, the content described is only for the purpose of facilitating the understanding of the embodiments adopted by the present application, and is not intended to limit the present application. Any person skilled in the art of the present application can make any modification and change in the form and details without departing from the spirit and scope of the present application. However, the protection scope of the present application shall be subject to the scope defined by the appended claims.

Claims

1. A method of manufacturing task service resource allocation, characterized by, The application relates to a method for determining an optimal service resource allocation scheme for a manufacturing task. The method comprises the following steps: a service resource allocation model is constructed with the minimum weighted value of total time cost and total fund cost of the manufacturing task in multiple service stages as the target and in combination with constraint conditions; a genetic algorithm is used to determine the optimal service resource allocation scheme for the manufacturing task based on the service resource allocation model; the service resource allocation model is constructed with the minimum weighted value of total time cost and total fund cost of the manufacturing task in multiple service stages as the target and in combination with constraint conditions, and the method comprises the following steps: wherein F is an objective function, T is the total time cost over the plurality of service stages, C is the total capital cost over the plurality of service stages, a weight factor for the total time cost, a weight factor for the total capital cost; a target function is constructed with the minimum weighted value of total time cost and total fund cost of the manufacturing task in multiple service stages as the target; wherein Tmax is a predetermined threshold of total time cost within the plurality of service stages; the constraint conditions comprise a total time cost constraint condition and a total fund cost constraint condition, and the total time cost constraint condition is expressed as: wherein Cmax is a predetermined threshold of total capital cost over the plurality of service phases; the total fund cost constraint condition is expressed as:

2. The method of claim 1, wherein, the constraint conditions further comprise a time coordination constraint condition and / or a regional coordination constraint condition. the genetic algorithm is used to determine the optimal service resource allocation scheme for the manufacturing task based on the service resource allocation model, and the method comprises the following steps: step S201: an initial population is constructed based on time cost and fund cost of the manufacturing task in each service stage; step S202: the fitness of the initial population is calculated according to the target function; step S203: it is judged whether iteration is terminated, if yes, step S206 is executed; otherwise, step S204 is performed; step S204: genetic operation is performed on the initial population to obtain a child population; step S205: the fitness of the child population is calculated according to the target function; 3. The method of claim 1, wherein, step S206: when iteration of all populations is terminated, the optimal solution of the service resource allocation model is output.

4. The method of claim 3, wherein, the service stages comprise a supplier service stage, a production service stage, a warehouse service stage, a large ship service stage and a small ship service stage. the time cost of the supplier service stage comprises material purchasing time of a supplier, and the fund cost of the supplier service stage comprises material purchasing cost of the supplier; the time cost of the production service stage comprises waiting time and service time of a production base, and the fund cost of the production service stage comprises production cost of the production base; the time cost of the warehouse service stage comprises material storage time and finished product storage time of a warehouse, and the fund cost of the warehouse service stage comprises material storage cost and finished product storage cost of the warehouse; the time cost of the large ship service stage comprises large ship time in a port, and the fund cost of the large ship service stage comprises booking cost of the large ship and transportation cost from the warehouse to the port where the large ship is located; 5. The method of claim 4, wherein, the time cost of the small ship service stage comprises small ship time in a port, and the fund cost of the small ship service stage comprises booking cost of the small ship and transportation cost from the warehouse to the port where the small ship is located. wherein TS represents the time synchronization strength; denotes meaningless time; i represents the number of manufacturing tasks, i = 1, 2, …, I; denotes the production start time of the production base, denotes the purchase arrival time of the supplier, denotes the material purchase start time of the supplier, denotes the production end time of the production base, denotes the actual departure time of the large ship at the port, denotes the time when the large ship starts work at the port.

6. The method of claim 4, wherein, the time coordination constraint condition comprises: the regional coordination constraint condition comprises: wherein, RS represents regional coordination strength of a production base and a warehouse, i represents the number of a manufacturing task, i=1, 2, …, I, and G is a positive number.

7. A storage medium, characterized by The storage medium has a computer program stored therein, and the computer program, when executed by a processor, implements the manufacturing task service resource allocation method of any one of claims 1 to 6.

8. An apparatus, comprising: A device comprises a memory and a processor, and the memory has a computer program stored therein, and the computer program, when executed by the processor, implements the manufacturing task service resource allocation method of any one of claims 1 to 6.

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