CN113706006B - Resource allocation method, device, equipment and storage medium for equipment production - Google Patents
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Abstract
The application discloses a resource allocation method, a device, equipment and a storage medium for equipment production, wherein the method comprises the steps of obtaining the priority execution relation and the theoretical operation time of each task in a target production line and the type and the quantity of resources required for completing each task; establishing an execution priority relation graph of each task based on the priority execution relation and the theoretical operation duration of each task; acquiring a key execution path and an executable interval matrix based on the execution priority relation graph of each task; and performing resource allocation on each task in the target production line based on the resource demand matrix and the executable interval matrix of each task to obtain a resource allocation result. The technical problem of inaccurate resource allocation of the existing equipment production is solved, the accuracy of the resource allocation of the equipment production line is improved, and the low resource utilization rate caused by the inaccuracy of the resource allocation is avoided.
Description
Technical Field
The present application relates to the field of device production technologies, and in particular, to a method, an apparatus, a device, and a storage medium for resource allocation in device production.
Background
For some large-scale special equipment production lines, the production line has the characteristics of strong production rhythm, multiple working types, narrow working face, high crossing of working contents and large influence of supply chain punctuality. In some important production links, accurate resource allocation is difficult to realize due to the characteristics of multiple resource constraint conditions and high possibility of disturbance.
Disclosure of Invention
The present application mainly aims to provide a method, an apparatus, a device and a storage medium for resource allocation in equipment production, and aims to solve the technical problem that resource allocation in existing equipment production is inaccurate.
In order to achieve the above object, the present application provides a resource allocation method for device production, including:
acquiring a priority execution relation and theoretical operation duration of each task in a target production line and the type and quantity of resources required for completing each task;
establishing an execution priority relation graph of each task based on the priority execution relation and the theoretical operation duration of each task;
obtaining a key execution path and an executable interval matrix based on the execution priority relation graph of each task;
performing resource allocation on each task in the target production line based on the resource demand matrix and the executable interval matrix of each task to obtain a resource allocation result; the resource demand matrix is generated based on the types and the quantity of the resources required for completing each task.
Optionally, the step of obtaining a key execution path and an executable interval matrix based on the execution priority relationship graph includes:
according to the execution priority relation graph of each task, obtaining the earliest execution time and the latest execution time of each task:
and obtaining a key execution path and an executable interval matrix according to the earliest execution time and the latest execution time of each task.
Optionally, the execution priority relationship graph is a directed acyclic graph, and the execution priority relationship graph includes an immediate relation and an immediate relation of each task;
the step of obtaining the earliest execution time and the latest execution time of each task according to the execution priority relationship diagram of each task comprises the following steps:
according to the immediate previous relation of each task, performing forward topological sorting on the execution priority relation graph of each task to obtain a forward linear task sequence meeting all the immediate previous relations;
according to the forward linear task sequence and the dynamic programming algorithm, solving the earliest execution time of each task one by one to obtain the earliest execution time of each task;
according to the close-after relation of each task, performing reverse topological sequencing on the execution priority relation graph of each task to obtain a reverse linear task sequence meeting all close-after relations;
and solving the latest execution time of each task one by one according to the reverse linear task sequence and the dynamic programming algorithm to obtain the latest execution time of each task.
Optionally, the step of obtaining the critical execution path according to the earliest execution time and the latest execution time of each task includes:
and taking a target task as a key execution path, wherein the target task is a task with zero time difference between the earliest execution time and the latest execution time.
Optionally, the step of performing resource allocation on each task in the target production line based on the resource demand matrix and the executable interval matrix of each task includes:
obtaining a resource configuration matrix according to the following relation:
R＝T AO ·R AO ＝[R km ]wherein, R represents a resource configuration matrix; matrix element R km The usage amount of the mth resource at the k moment is shown; t is a unit of AO Representing a matrix of executable intervals, R AO Representing a resource demand matrix;
and according to the resource allocation matrix, performing resource allocation on each task in the target production line.
Optionally, after the step of performing resource allocation on each task in the target production line based on the resource demand matrix and the executable interval matrix of each task to obtain a resource allocation result, the method further includes:
and adjusting the resource configuration result according to the executable slots of each task to obtain the adjusted resource configuration result.
Optionally, the step of adjusting the resource configuration result according to the executable slots of each task to obtain the adjusted resource configuration result includes:
adjusting the usage amount of the resource in the resource configuration matrix according to the following relation:
according to R' km And adjusting the resource configuration result to obtain the adjusted resource configuration result.
In addition, to achieve the above object, the present application further provides a resource allocation device for device production, including:
the data acquisition module is used for acquiring the prior execution relation and the theoretical operation time of each task in the target production line and the type and the quantity of resources required for completing each task;
the relation establishing module is used for establishing an execution priority relation graph of each task based on the priority execution relation and the theoretical operation duration of each task;
the path obtaining module is used for obtaining a key execution path and an executable interval matrix based on the execution priority relation graph of each task;
the resource allocation module is used for allocating resources for each task in the target production line based on the resource demand matrix of each task and the executable interval matrix so as to obtain a resource allocation result; the resource demand matrix is generated based on the types and the quantity of the resources required for completing each task.
In addition, to achieve the above object, the present application further provides a production apparatus, which includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above method.
In addition, to achieve the above object, the present application further provides a computer readable storage medium, where a computer program is stored, and a processor executes the computer program to implement the above method.
The beneficial effect that this application can realize.
The method comprises the steps of obtaining a priority execution relation and theoretical operation duration of each task in a target production line and the type and quantity of resources required for completing each task; establishing an execution priority relation graph of each task based on the priority execution relation and the theoretical operation duration of each task; acquiring a key execution path and an executable interval matrix based on the execution priority relation graph of each task; performing resource allocation on each task in the target production line based on the resource demand matrix and the executable interval matrix of each task to obtain a resource allocation result; the resource demand matrix is generated based on the types and the quantity of the resources required for completing each task. That is, according to objective data of the production line, by establishing an execution priority relationship diagram, obtaining a key execution path, an executable interval matrix and a resource demand matrix, and other theoretical methods, resource allocation is performed in advance, and compared with the prior art that resources are allocated according to experience, the technical problem that resource allocation of the existing equipment production is inaccurate is solved, the accuracy of resource allocation of the equipment production line is improved, and the low resource utilization rate caused by inaccuracy of resource allocation is avoided.
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FIG. 1 is a schematic diagram of a production facility in a hardware operating environment according to an embodiment of the present disclosure;
FIG. 2 is a schematic flow chart illustrating a resource allocation method for equipment production according to an embodiment of the present disclosure;
FIG. 3 is a schematic diagram illustrating an execution priority relationship according to an embodiment of the present application;
fig. 4 is a schematic functional block diagram of a resource allocation device produced by the apparatus according to the embodiment of the present application.
The implementation, functional features and advantages of the objectives of the present application will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The main solution of the embodiment of the application is as follows: acquiring a priority execution relation and theoretical operation duration of each task in a target production line, and the type and the quantity of resources required for completing each task; establishing an execution priority relation graph of each task based on the priority execution relation and the theoretical operation duration of each task; acquiring a key execution path and an executable interval matrix based on the execution priority relation graph of each task; performing resource allocation on each task in the target production line based on the resource demand matrix and the executable interval matrix of each task to obtain a resource allocation result; the resource demand matrix is generated based on the types and the quantity of the resources required for completing each task.
In the prior art, the resources are configured according to the experience based on the prior data. However, because the production line of some special equipment (such as an airplane general assembly) has the characteristics of strong rhythm of production, multiple working types, narrow working surface, highly crossed working contents and great influence by the timeliness of a supply chain, the production line capacity is difficult to accurately estimate due to the characteristics of multiple resource constraint conditions and easy disturbance.
The resource allocation method comprises the steps of obtaining a key execution path, an executable interval matrix and a resource demand matrix by establishing an execution priority relation graph according to objective data of a production line and other theoretical methods, so as to allocate resources in advance, and compared with the prior art that resources are allocated according to experience, the technical problem that the resource allocation of the existing equipment production is inaccurate is solved, the accuracy of the resource allocation of the equipment production line is improved, and the low resource utilization rate caused by the inaccuracy of the resource allocation is avoided.
Referring to fig. 1, fig. 1 is a schematic structural diagram of a production device in a hardware operating environment according to an embodiment of the present application.
As shown in fig. 1, the production apparatus may include: a processor 1001, such as a Central Processing Unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to implement connection communication among these components. The user interface 1003 may include a Display (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a WIreless interface (e.g., a WIreless-FIdelity (WI-FI) interface). The Memory 1005 may be a Random Access Memory (RAM) Memory, or may be a Non-Volatile Memory (NVM), such as a disk Memory. The memory 1005 may alternatively be a storage device separate from the processor 1001 described previously.
Those skilled in the art will appreciate that the configuration shown in FIG. 1 does not constitute a limitation of the production apparatus and may include more or fewer components than shown, or some components may be combined, or a different arrangement of components.
As shown in fig. 1, the memory 1005, which is a storage medium, may include therein an operating system, a data storage module, a network communication module, a user interface module, and an electronic program.
In the production apparatus shown in fig. 1, the network interface 1004 is mainly used for data communication with a network server; the user interface 1003 is mainly used for data interaction with a user; the processor 1001 and the memory 1005 in the production apparatus of the present invention may be disposed in the production apparatus, and the production apparatus invokes, through the processor 1001, a resource allocation device for device production stored in the memory 1005, and executes the resource allocation method for device production provided in the embodiment of the present application.
Referring to fig. 2, based on the hardware device of the foregoing embodiment, an embodiment of the present application provides a resource allocation method for device production, including:
s20, acquiring a priority execution relation and theoretical operation duration of each task in a target production line, and types and quantity of resources required for completing each task;
in the implementation, the target production line may be any production line, which is not limited in this embodiment, but as an embodiment, the target production line refers to an assembly production line of large feature devices, such as a final assembly production line of an aircraft.
In the present embodiment, the explanation of each step is given by taking the assembly line of the aircraft as an example, but the explanation is not limited thereto.
Therefore, in the present embodiment, the final assembly line of the aircraft generally includes multiple assembly tasks (AO), and there are a priority execution relationship between the tasks, a theoretical operation duration, and the types and amounts of resources required to complete the tasks.
Specifically, all AOs and execution bays are numbered. An immediate preceding relation set of each AO is given through process simulation and expert knowledge, theoretical operation duration and execution cabin space of each AO are collected, and data samples are as follows:
TABLE 1 AO priority execution relationship, theoretical operation duration, execution bay information collection Table
In addition, the AO performs the collection of the type and amount of resources required: data collection and numbering are carried out on resources required by each assembly task, the related resources comprise personnel, tools, equipment, materials and the like, and data samples are as follows, for example, in the following table 2:
table 2 AO resource requirement information collecting table
As an embodiment, the resource requirement matrix of the AO may be given according to the kind and number of resources required to complete each task. For example, according to table 2, the matrix is defined as follows: r is AO ＝[R 1 ,R 2 ,R 3 ,R 4 ,R 5 ]＝[r im ]Wherein R is AO The resource demand matrix is NxM order in size, N is the number of AO, and M is the number of all resource types; r 1 ,R 2 ,R 3 ,R 4 ,R 5 The block matrixes respectively represent resources such as personnel, tools, equipment, materials and the like, and the size of each block matrix is NxM 1 ,N×M 2 ,N×M 3 ,N×M 4 ,N×M 5 Order, M 1 ,M 2 ,M 3 ,M 4 ,M 5 Respectively representing the kinds of resources such as personnel, tools, equipment, materials and the like, wherein M = M 1 +M 2 +M 3 +M 4 +M 5 ；[r im ]Representing a matrix R AO Row I and column m elements in (1), i.e. the requirement of the mth resource of AO numbered I.
It should be noted that establishing the AO priority execution relationship, the theoretical operation duration, and the execution bay information collection table can provide objective basic data for subsequent theoretical calculation to ensure that the subsequent theoretical calculation obtains an accurate result. In addition, the resource demand matrix is established, so that the subsequent theoretical calculation can be performed by directly utilizing a matrix operation mode, and the calculation efficiency can be improved.
S40, establishing an execution priority relation graph of each task based on the priority execution relation and the theoretical operation duration of each task;
in a specific implementation process, an execution priority relationship diagram of each task may be established according to the foregoing table 1. Specifically, the assembly priority relationship of the AOs can be represented as a directed graph G = { V, E }, where V is a set of vertices representing all AOs; e is a directed edge set, represents the priority assembly relationship between the AO, sets the weight of each edge, and represents the execution duration of the AO. Referring to fig. 3, fig. 3 is an execution priority relationship diagram of the present embodiment, in which an arrow with a directed edge indicates an AO immediately before, and an arrow tail indicates an AO immediately after; directed edge e ij The weight of is t i Indicates the theoretical execution time period of the ith own AO.
It should be noted that, establishing a directed execution priority relationship diagram is more intuitive, and facilitates subsequent calculation of the critical path and the execution interval.
And S60, acquiring a key execution path and an executable interval matrix based on the execution priority relation graph.
In a specific implementation process, after the execution priority relationship diagram is established, for the requirement of subsequent resource configuration calculation, a key execution path and an executable interval matrix need to be obtained based on the execution priority relationship diagram.
Considering that the number of the AO of the aircraft final assembly is large, the assembly priority relationship is complex, the complexity of traversing all the nodes for solving is high, and the n! The problem of node combination is NP difficult problem, which can not be solved in linear time. Therefore, according to the idea of the dynamic programming algorithm, the following method is provided to obtain the earliest execution time (earliest start time), the latest execution time (latest start time) and the critical path of the AO.
In one embodiment, the step of obtaining a key execution path and an executable interval matrix based on the execution priority relationship graph includes:
firstly, according to the execution priority relation graph of each task, obtaining the earliest execution time and the latest execution time of each task:
specifically, in this embodiment, the execution priority relationship graph is a directed acyclic graph, and the execution priority relationship graph includes an immediate relation and an immediate relation of each task; the step of obtaining the earliest execution time and the latest execution time of each task according to the execution priority relationship diagram of each task comprises the following steps:
according to the immediate previous relation of each task, performing forward topological sorting on the execution priority relation graph of each task to obtain a forward linear task sequence meeting all the immediate previous relations;
according to the forward linear task sequence and the dynamic programming algorithm, solving the earliest execution time of each task one by one to obtain the earliest execution time of each task;
according to the tight relations of all the tasks, performing reverse topological sorting on the execution priority relation graph of all the tasks to obtain a reverse linear task sequence meeting all the tight relations;
and solving the latest execution time of each task one by one according to the reverse linear task sequence and the dynamic programming algorithm to obtain the latest execution time of each task.
In the specific implementation process:
1. AO performs time calculation earliest:
according to the tight front relation set of AO, the topological sorting is carried out to the directed acyclic graph of AO, and a total order on the set is obtained by the partial order on the AO relation set, that is, a linear AO sequence satisfying all tight front relations is found, the concrete method is as follows:
step1: searching all nodes with the degree of 0, and after the searching is finished, recording the result to a topological sequence number set (if the degree of 0 of a plurality of nodes exists, the nodes with smaller marks can be recorded first);
step2: deleting the nodes and the adjacent edges thereof recorded in the topological sequence, and returning to Step1 after updating the data until all the nodes are recorded in the topological sequence.
And numbering each AO again according to the obtained sequence of the topological ordering, and taking the number as the searching sequence of the dynamic programming algorithm.
The conversion formula for solving the earliest execution time by dynamic programming is as follows:
in this equation dist [ u ]]Represents the earliest execution time of the u-th main AO, edge [ v ]][u]Representing the weight of a directed edge from v to u, i.e. the theoretical execution duration t of an AO numbered v v 。
The problem is converted into the earliest execution time of the AO with the reference number v by using the formula, so that the earliest execution time of the AO is changed into a small sub-problem, the earliest execution time problem of all the AO can be converted and reduced, and the simplest problem is finally obtained, namely the theoretical execution duration problem of each AO, the thinking direction of the algorithm is from complex to simple, the design of the algorithm is from simple to complex, and the specific algorithm design of the earliest execution time of the AO is as follows:
step1: giving all AO initial values, setting the earliest starting time dist [1] =0 of a source point in the topological sorting, and setting other values to-infinity, so that comparison and updating are performed on data after an optimal solution is obtained;
step2: conversion formula according to topological sorting order and dynamic programming algorithm
Solving for the earliest execution time of AO one by one。
2. AO latest execution time calculation
Similar to the calculation method of the earliest execution time, firstly, a sink starts to generate a reverse AO topological sorting, the latest execution time allowed by each node is calculated one by one according to the reverse topological sorting, and a conversion formula for solving the latest execution time by dynamic planning is as follows:
in this formula, dist [ u ]]Represents the latest execution time of the u-th own AO, edge [ v ]][u]Denotes the theoretical AO execution duration t numbered v v T is the maximum of all the earliest execution times, with the initial value set dist [1]]= T, other values are set to + ∞, and specific algorithm steps are not described herein again.
And then, obtaining a key execution path and an executable interval matrix according to the earliest execution time and the latest execution time of each task.
Specifically, the step of obtaining the key execution path according to the earliest execution time and the latest execution time of each task includes:
and taking a target task as a key execution path, wherein the target task is a task with zero time difference between the earliest execution time and the latest execution time.
And calculating the AO start floating value according to the obtained earliest execution time and latest execution time of the AO, wherein the formula is as follows:
Δ i ＝LT i -ET i
wherein, delta i Represents the start-up float value, LT, of the ith own AO i Represents the latest execution time, ET, of the ith own AO i Represents the earliest execution time of the ith host AO if Delta i =0, then the subject AO is a critical path AO; the execution section of the ith local AO is [ LT i ，ET i ]And the AO does not influence the delivery cycle when operating and executing at any time in the interval.
Further, the executable interval matrix may be obtained according to the following method:
firstly, discretizing time according to data characteristics of theoretical execution duration of the AO and considering calculation cost of a subsequent planning algorithm, in this embodiment, a minimum interval unit of time is defined as 0.5 hour, and a time sequence set is T = { T = 1 ,T 2 Venture. } = {0,0.5,1, 1.5. Giving the matrix T of executable intervals of the AO according to the earliest and latest execution time of each AO AO The matrix is defined as follows:
each column in the matrix is the executable state of all AOs at the moment, and 0 means not in the executable interval, and 1 means in the executable interval.
In a specific implementation process, the critical execution path and the executable area of each task can be represented in a graph form.
S80, performing resource allocation on each task in the target production line based on the resource demand matrix of each task and the executable interval matrix to obtain a resource allocation result; the resource demand matrix is generated based on the types and the quantity of the resources required for completing each task.
In a specific implementation process, the step of performing resource allocation on each task in the target production line based on the resource demand matrix and the executable interval matrix of each task includes:
obtaining a resource configuration matrix according to the following relation:
R＝T AO ·R AO ＝[R km ]wherein, R represents a resource configuration matrix; matrix element R km The usage amount of the mth resource at the k moment is shown; t is a unit of AO Representing a matrix of executable intervals, R AO Representing a resource demand matrix;
and according to the resource allocation matrix, performing resource allocation on each task in the target production line.
In one embodiment, after the step of performing resource allocation on each task in the target production line based on the resource demand matrix and the executable interval matrix of each task to obtain a resource allocation result, the method further includes:
and adjusting the resource configuration result according to the executable slots of each task to obtain the adjusted resource configuration result.
It should be noted that, because the general assembly operation of the aircraft has the characteristics of poor opening of the execution bay and small operation space, the parallel execution operation of the AO in the executable section is limited. Based on this, in order to meet the demand of resources more accurately, the demand of resources at each time is adjusted.
Specifically, the step of adjusting the resource configuration result according to the executable slots of each task to obtain the adjusted resource configuration result includes:
adjusting the usage amount of the resource in the resource configuration matrix according to the following relation:
according to R' km And adjusting the resource configuration result to obtain the adjusted resource configuration result. Adjusting the usage amount of the resource according to the relational expression, namely under the condition that the AO is normally started, the maximum demand amount of M kinds of resources at each moment is the configuration amount of the resource, wherein M is the later 5 The item resource allocation is the optimal stock of each material under the limit production capacity.
It should be understood that the above is only an example, and the technical solution of the present application is not limited in any way, and those skilled in the art can set the solution based on the needs in practical application, and the solution is not limited herein.
Through the above description, it is not difficult to find that the method of this embodiment performs resource allocation in advance by establishing an execution priority relationship diagram according to objective data of a production line and by obtaining theoretical methods such as a key execution path, an executable interval matrix, and a resource demand matrix, and compared with the prior art that resources are allocated according to experience, the method solves the technical problem that resource allocation of existing equipment production is inaccurate, achieves the purpose of improving the accuracy of resource allocation of an equipment production line, and avoids low resource utilization rate caused by inaccuracy of resource allocation.
Referring to fig. 4, based on the same inventive concept, an embodiment of the present application further provides a device for resource allocation in device production, including:
the data acquisition module is used for acquiring the prior execution relation and the theoretical operation time of each task in the target production line and the type and the quantity of resources required for completing each task;
the relation establishing module is used for establishing an execution priority relation graph of each task based on the priority execution relation and the theoretical operation duration of each task;
the path obtaining module is used for obtaining a key execution path and an executable interval matrix based on the execution priority relation graph of each task;
the resource allocation module is used for allocating resources for each task in the target production line based on the resource demand matrix of each task and the executable interval matrix so as to obtain a resource allocation result; the resource demand matrix is generated based on the types and the quantity of the resources required for completing each task.
It should be noted that, in this embodiment, each module in the resource allocation device for device production corresponds to each step in the resource allocation method for device production in the foregoing embodiment one by one, and therefore, the specific implementation of this embodiment may refer to the implementation of the resource allocation method for device production, which is not described herein again.
It should be understood that the above is only an example, and the technical solution of the present application is not limited in any way, and those skilled in the art can set the solution based on the needs in practical application, and the solution is not limited herein.
Through the above description, it is not difficult to find that the device of this embodiment performs resource allocation in advance by establishing an execution priority relationship diagram according to objective data of a production line and by obtaining theoretical methods such as a key execution path, an executable interval matrix, and a resource demand matrix, and compared with the prior art that resources are allocated according to experience, the device solves the technical problem that resource allocation of existing equipment production is inaccurate, achieves the purpose of improving the accuracy of resource allocation of an equipment production line, and avoids low resource utilization rate caused by inaccuracy of resource allocation.
Furthermore, in an embodiment, there is also provided a production device comprising a processor, a memory and a computer program stored in the memory, which computer program, when executed by the processor, implements the steps of the method in the preceding embodiments.
Furthermore, in an embodiment, the present application further provides a computer storage medium having a computer program stored thereon, where the computer program is executed by a processor to implement the steps of the method in the foregoing embodiments.
In some embodiments, the computer-readable storage medium may be memory such as FRAM, ROM, PROM, EPROM, EEPROM, flash, magnetic surface memory, optical disk, or CD-ROM; or may be various devices including one or any combination of the above memories. The computer may be a variety of computing devices including intelligent terminals and servers.
In some embodiments, the executable instructions may be in the form of a program, software module, script, or code written in any form of programming language, including compiled or interpreted languages, or declarative or procedural languages, and it may be deployed in any form, including as a stand-alone program or as a module, component, subroutine, or other unit suitable for use in a computing environment.
By way of example, executable instructions may correspond, but do not necessarily have to correspond, to files in a file system, and may be stored in a portion of a file that holds other programs or data, such as in one or more scripts in a hypertext Markup Language (HTML) document, in a single file dedicated to the program in question, or in multiple coordinated files (e.g., files that store one or more modules, sub-programs, or portions of code).
As an example, executable instructions may be deployed to be executed on one computing device or on multiple computing devices located at one site or distributed across multiple sites and interconnected by a communication network.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrases "comprising a," "8230," "8230," or "comprising" does not exclude the presence of other like elements in a process, method, article, or system comprising the element.
The above-mentioned serial numbers of the embodiments of the present application are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present application or portions thereof contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium (such as a rom/ram, a magnetic disk, and an optical disk) and includes instructions for enabling a multimedia terminal (such as a mobile phone, a computer, a television receiver, or a network device) to execute the method described in the embodiments of the present application
The above description is only a preferred embodiment of the present application, and not intended to limit the scope of the present application, and all the equivalent structures or equivalent processes that can be directly or indirectly applied to other related technical fields by using the contents of the specification and the drawings of the present application are also included in the scope of the present application.
Claims (8)
1. A resource allocation method for equipment production, comprising:
acquiring a priority execution relation and theoretical operation duration of each task in a target production line and the type and quantity of resources required for completing each task;
establishing an execution priority relation graph of each task based on the priority execution relation and the theoretical operation duration of each task; wherein, the execution priority relation graph is a directed graph;
acquiring a key execution path and an executable interval matrix based on the execution priority relation graph of each task;
performing resource allocation on each task in the target production line based on the resource demand matrix and the executable interval matrix of each task to obtain a resource allocation result; the resource demand matrix is generated based on the type and the quantity of resources required for completing each task;
wherein the step of obtaining a key execution path and an executable interval matrix based on the execution priority relationship graph comprises: according to the execution priority relation graph of each task, obtaining the earliest execution time and the latest execution time of each task: obtaining a key execution path and an executable interval matrix T according to the earliest execution time and the latest execution time of each task AO An interval matrix T can be executed AO The definition is as follows:
wherein the interval matrix T can be executed AO Each column in the sequence is whether each task at the moment k is in an executable state, 0 represents that each task is not in an executable interval, and 1 represents that each task is in an executable intervalWithin the execution interval;
the step of performing resource allocation on each task in the target production line based on the resource demand matrix and the executable interval matrix of each task comprises the following steps: obtaining a resource configuration matrix according to the following relation: r = T AO ·R AO ＝[R km ]Wherein, R represents a resource configuration matrix; matrix element R km The usage amount of the mth resource at the k moment is shown; t is a unit of AO Representing a matrix of executable intervals, R AO Representing a resource demand matrix; and according to the resource allocation matrix, performing resource allocation on each task in the target production line.
2. The method of claim 1, wherein the execution priority relationship graph is a directed acyclic graph, and the execution priority relationship graph includes an immediate before relationship and an immediate after relationship for each task;
the step of obtaining the earliest execution time and the latest execution time of each task according to the execution priority relation graph of each task comprises the following steps:
according to the immediate previous relation of each task, performing forward topological sorting on the execution priority relation graph of each task to obtain a forward linear task sequence meeting all the immediate previous relations;
according to the forward linear task sequence and the dynamic programming algorithm, solving the earliest execution time of each task one by one to obtain the earliest execution time of each task;
according to the tight relations of all the tasks, performing reverse topological sorting on the execution priority relation graph of all the tasks to obtain a reverse linear task sequence meeting all the tight relations;
and solving the latest execution time of each task one by one according to the reverse linear task sequence and the dynamic programming algorithm to obtain the latest execution time of each task.
3. The method of claim 2, wherein the step of obtaining a critical execution path based on the earliest execution time and the latest execution time of each task comprises:
and taking a target task as a key execution path, wherein the target task is a task with zero time difference between the earliest execution time and the latest execution time.
4. The method of claim 3, wherein after the step of performing resource allocation on each task in the target production line based on the resource demand matrix and the executable interval matrix of each task to obtain a resource allocation result, the method further comprises:
and adjusting the resource configuration result according to the executable slots of each task to obtain the adjusted resource configuration result.
5. The method according to claim 4, wherein the step of adjusting the resource allocation result according to the executable slots of each task to obtain the adjusted resource allocation result comprises:
adjusting the usage amount of the resource in the resource configuration matrix according to the following relation:
according to R' km And adjusting the resource configuration result to obtain the adjusted resource configuration result.
6. A resource allocation apparatus for plant production, comprising:
the data acquisition module is used for acquiring the prior execution relation and the theoretical operation time of each task in the target production line and the type and the quantity of resources required for completing each task;
the relation establishing module is used for establishing an execution priority relation graph of each task based on the priority execution relation and the theoretical operation duration of each task; wherein, the execution priority relation graph is a directed graph;
the path obtaining module is used for obtaining a key execution path and an executable interval matrix based on the execution priority relation graph of each task;
the resource allocation module is used for performing resource allocation on each task in the target production line based on the resource demand matrix and the executable interval matrix of each task to obtain a resource allocation result; the resource demand matrix is generated based on the type and the quantity of resources required for completing each task;
the path obtaining module is specifically configured to obtain the earliest execution time and the latest execution time of each task according to the execution priority relationship diagram of each task: obtaining a key execution path and an executable interval matrix T according to the earliest execution time and the latest execution time of each task AO Can execute the interval matrix T AO The definition is as follows:
wherein the interval matrix T can be executed AO Each column in the sequence is whether each task is in an executable state at the moment k, 0 represents that the task is not in an executable interval, and 1 represents that the task is in the executable interval;
wherein the resource configuration module is specifically configured to: obtaining a resource configuration matrix according to the following relation: r = T AO ·R AO ＝[R km ]Wherein, R represents a resource configuration matrix; matrix element R km The usage amount of the mth resource at the k moment is shown; t is a unit of AO Representing a matrix of executable intervals, R AO Representing a resource demand matrix; and according to the resource allocation matrix, performing resource allocation on each task in the target production line.
7. A production device, characterized in that it comprises a memory in which a computer program is stored and a processor which executes said computer program implementing the method according to any one of claims 1-5.
8. A computer-readable storage medium, having stored thereon a computer program, which, when executed by a processor, performs the method of any one of claims 1-5.
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