Hybrid flow shop scheduling optimization method

A technology for workshop scheduling and optimization methods, applied in the direction of control/regulation systems, instruments, and comprehensive factory control, etc., can solve problems such as difficulties, and achieve the effects of improving production efficiency, ensuring search capabilities, and improving search efficiency

Active Publication Date: 2021-12-03
FUZHOU UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

Solving such problems not only needs to consider arranging suitable machines for each process, but also considers the order in which workpieces are processed on each machine, which is a more difficult NP-hard problem

Method used

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  • Hybrid flow shop scheduling optimization method
  • Hybrid flow shop scheduling optimization method
  • Hybrid flow shop scheduling optimization method

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Embodiment Construction

[0076] The invention will be further described below with reference to the accompanying drawings and examples.

[0077] Please refer to figure 1 The present invention provides a figure 1 As shown, this embodiment provides a method of dispatching optimization of a mixed water workshop, specifically comprising the steps of:

[0078] Step S1: Description of the symbols of the production scheduling problem between multi-target water workshops;

[0079] Step S2: Establish constraints must be met during production optimization;

[0080] Step S3: Determine the target to be optimized, establish a corresponding multi-objective optimization function;

[0081] Step S4: Design Based on the Multi-Objective Best Food Algorithm (Optimal Foraging Algorithm, Optimal Foraging Algorithm, OFA Algorithm);

[0082] Step S5: Perform iterative optimization operation, output Pareto optimal solution;

[0083] Step S6: Obtain the best schedule according to the optimization result of step S5.

[0084] In the...

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Abstract

The invention relates to a hybrid flow shop scheduling optimization method. The method comprises the following steps: S1, converting a multi-target flow shop production scheduling problem into formalized description of numeric symbols; S2, establishing a preset constraint condition for production optimization; S3, obtaining a to-be-optimized target, and establishing a corresponding multi-target optimization function; S4, constructing an improved multi-target optimal foraging algorithm based on combination of a regret theory, a disappropriation theory and a VIKOR decision-making method; S5, performing iterative optimization operation based on the multi-objective optimization function and the improved multi-objective optimal foraging algorithm, and outputting a Pareto optimal solution set; and S6, according to an optimization result of the step S5, obtaining an optimal scheduling arrangement. According to the invention, a better scheduling scheme can be quickly and effectively obtained, and the workshop production efficiency is improved.

Description

Technical field [0001] The present invention relates to a technical field of production scheduling discrete manufacturing system, particularly relates to a method for mixing flow shop scheduling optimization. Background technique [0002] Hybrid Flowshop Scheduling (Hybrid Flow Shop Scheduling Problem, HFSP) can be seen as a combination of classical flow shop scheduling problem and parallel machine scheduling problems in the study HFSP, in addition to reducing completion time, should consider the utilization and improve processing quality and reduce plant energy consumption. Mixed flow shop scheduling problem, a step may not only be localized on one machine, but the machine may be selected from a plurality of parallel processing machines. To solve such problems not only consider arranging a suitable machine for each procedure, but also consider the order on each machine workpieces, it is more difficult NP-hard problem. Inventive content [0003] In view of this, object of the pr...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B19/418
CPCG05B19/41865G05B2219/32247Y02P90/30
Inventor 朱光宇刘志
Owner FUZHOU UNIV
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