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Flow shop scheduling method based on combination of genetic algorithm and particle swarm optimization

A particle swarm algorithm and workshop scheduling technology, applied in the direction of comprehensive factory control, comprehensive factory control, electrical program control, etc., can solve the problems of low search accuracy and local minimum, and achieve increased evolution quality, increased convergence speed, shortened The effect of convergence time

Pending Publication Date: 2022-04-12
FUZHOU UNIVERSITY
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Problems solved by technology

However, it is prone to premature, falling into local minimum and the search accuracy in the later stage is not high

Method used

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  • Flow shop scheduling method based on combination of genetic algorithm and particle swarm optimization
  • Flow shop scheduling method based on combination of genetic algorithm and particle swarm optimization
  • Flow shop scheduling method based on combination of genetic algorithm and particle swarm optimization

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Embodiment Construction

[0036] The technical solution of the present invention will be specifically described below in conjunction with the accompanying drawings.

[0037] A kind of flow shop scheduling method based on the combination of genetic algorithm and particle swarm algorithm of the present invention comprises the following steps:

[0038] Step 1: Introduce the weight coefficient in the particle swarm optimization algorithm;

[0039] Step 2: Model the flow workshop, that is, in the flow processing process of n workpieces on m machines, each part is processed in the same order on each machine, and it is agreed that each workpiece is only processed once on each machine. Each machine can only process one workpiece at a time, the processing time and preparation time required for each workpiece on each machine are known, and the processing completion time is the shortest when the corresponding scheduling plan is required;

[0040] Step 3: Apply the particle swarm optimization algorithm to the flo...

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Abstract

The invention relates to a flow shop scheduling method based on combination of a genetic algorithm and a particle swarm algorithm. The method is suitable for the field of workshop scheduling, the particle swarm algorithm and the genetic algorithm are combined according to the defects that precocity is prone to occurring, the convergence speed is low, and the later search performance and the individual optimization capacity are reduced, the diversity of particles is improved, the possibility that the algorithm is caught in local optimum due to the fact that later populations are too dense is reduced, and the optimization efficiency is improved. The evolutionary process is accelerated, and the convergence efficiency and the group search performance are improved.

Description

technical field [0001] The invention relates to the field of path planning workshop scheduling, in particular to a flow workshop scheduling method based on the combination of genetic algorithm and particle swarm algorithm. Background technique [0002] A flow workshop refers to a production workshop that is arranged according to a flow-type production line and includes multiple processes and each process has one or more parallel machines. It is also called a flexible flow workshop. This kind of workshop structure can effectively eliminate the impact of bottleneck machines on production continuity and improve the efficiency of the entire production line. Therefore, how to minimize the time consumption of the assembly line is the focus and difficulty of research. To solve the scheduling problem of the flow shop, there are mainly two aspects: one is coding, and the other is the selection of algorithms. [0003] Many algorithms and methods are used to solve the job shop schedul...

Claims

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Application Information

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IPC IPC(8): G05B19/418
CPCY02P90/02
Inventor 涂俊翔陈波
Owner FUZHOU UNIVERSITY
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