Distributed blocking flow workshop scheduling method and system considering assembly stages and energy consumption

A workshop scheduling and distributed technology, applied in the direction of control/regulation system, general control system, genetic law, etc., can solve the problems of workshop scheduling method not realizing global search and local search, reducing workshop scheduling efficiency, increasing energy consumption, etc. Achieve the effect of enhancing the global search ability, improving the efficiency of workshop scheduling, and accurate workshop scheduling

Active Publication Date: 2021-09-03
SHANDONG NORMAL UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] First, the existing workshop scheduling method does not consider the assembly stage and total energy consumption, which leads to inaccurate workshop scheduling, reduces the efficiency of workshop scheduling, increases the completion time, and increases energy consumption;
[0006] Second, the existing shop-floor scheduling methods do not implement global search and local search, resulting in slow generation of scheduling plans

Method used

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  • Distributed blocking flow workshop scheduling method and system considering assembly stages and energy consumption
  • Distributed blocking flow workshop scheduling method and system considering assembly stages and energy consumption
  • Distributed blocking flow workshop scheduling method and system considering assembly stages and energy consumption

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0042] This embodiment provides a distributed blocking water buffet scheduled method for a belt-fitting phase and a power consumption;

[0043] Distributed blocked water workshop scheduling method, including:

[0044] S101: Get parameters in distributed blocking water workshops;

[0045] S102: Based on the parameters of the distributed blocked water workshop, the scheduling model of the distributed blocking water workshop; the scheduling model of the distributed blocking water workshop, including: target functions and constraints;

[0046] S103: Based on the improved non-disparison sorting generating algorithm (NSGA-II), solving distributed blocked water workshop scheduling models, solving each individual as a solution during solving; after solving, the last iterative generation All non-dominable solutions in the concentrated are allowed to be considered optimal;

[0047] Among them, the improved non-disparison sorting genetic algorithm refers to an improved cross-and variant stra...

Embodiment 2

[0244] This embodiment provides a distributed blocked water buffore scheduling system with a packaging stage and a power consumption;

[0245] Distributed blocking water workshop scheduling system with mounting stages and energy consumption, including:

[0246] Get the module, which is configured to obtain parameters between distributed blocking water workshops;

[0247] The construction module is configured to: construct a scheduling model between distributed blocked water workshop based on the distributed blocking water workshop; the scheduling model of the distributed blocking water workshop, including: target function and constraints;

[0248] The solve module is configured to be: based on improved non-disparison sorting genetic algorithm, solving distributed blocked water workshop scheduling models, solving each individual as a solution during solving; after solving, the last iteration is generated by non-domain All non-dominable solutions that decompose are allowed to be con...

Embodiment 3

[0252]This embodiment also provides an electronic device comprising: one or more processors, one or more memories, and one or more computer programs; wherein the processor is connected to a memory, the above one or more computer programs areStored in the memory, when the electronic device is run, the processor performs one or more computer programs stored in the memory to enable the electronic device to perform the method described above.

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Abstract

The invention discloses a distributed blocking flow workshop scheduling method and system considering assembly stages and energy consumption. The method comprises the steps that: a scheduling model of a distributed blocking flow workshop is constructed based on the parameters of the distributed blocking flow workshop, the scheduling model of the distributed blocking flow workshop comprises an objective function and a constraint condition; based on an improved non-dominated sorting genetic algorithm, the distributed blocking flow workshop scheduling model is solved, and each individual is assumed as a solution in the solving process; and all non-dominated solutions in a non-dominated solution set generated by the last iteration are allowed to be regarded as optimal schemes. According to the improved non-dominated sorting genetic algorithm, the global search capability is improved by adopting a crossover and mutation strategy of the improved genetic algorithm; a local search strategy is adopted to enhance the convergence capability of the algorithm. According to the workshop scheduling method, the assembly stages and the total energy consumption are considered, workshop scheduling is accurate, the workshop scheduling efficiency is improved, the completion time is shortened, and the energy consumption is reduced.

Description

Technical field [0001] The present invention relates to the field of production scheduling techniques, and in particular, a distributed blocked water buffet scheduled method and system for a belt-fitting phase and a power consumption. Background technique [0002] The statement of this section is merely a background technique associated with the present invention and does not necessarily constitute a prior art. [0003] Distributed blocking water workshop scheduling as an extension of workshop scheduling issues to achieve extensive research. At the same time, different algorithms are also applied to distributed water workshop scheduling, and the present invention can divide these algorithms into accurate algorithms, heuristic algorithms, and element heuristic algorithms. Here, the present invention is mainly studied in the element heuristic algorithm. [0004] The inventors have found that the prior art has the following technical issues: [0005] First, the existing workshop sch...

Claims

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Application Information

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IPC IPC(8): G05B19/418G06N3/12
CPCG05B19/41885G06N3/126G05B2219/32339Y02P90/02
Inventor 李俊青牛唯于辉
Owner SHANDONG NORMAL UNIV
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