Method for scheduling machine part processing line by adopting discrete quantum particle swarm optimization

A particle swarm algorithm, discrete quantum technology, applied in the field of machine parts processing pipeline scheduling based on discrete quantum particle swarm algorithm

Inactive Publication Date: 2011-05-25
ZHEJIANG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0007] The purpose of the present invention is to effectively solve the optimization problem of machine parts processing pipeline scheduling,

Method used

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  • Method for scheduling machine part processing line by adopting discrete quantum particle swarm optimization
  • Method for scheduling machine part processing line by adopting discrete quantum particle swarm optimization
  • Method for scheduling machine part processing line by adopting discrete quantum particle swarm optimization

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Experimental program
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Effect test

Embodiment

[0094] The method of the present invention is used for the scheduling of the bearing processing sequence as follows, and is further described in detail:

[0095] To process four kinds of bearings (that is, workpieces) A, B, C, and D, according to the processing technology, it is necessary to turn first and then mill. The processing time is shown in the table below. There is a lathe and a milling machine , it is necessary to determine the optimal processing sequence of these four bearings

[0096] artifact name

lathe Working hours / h

milling machine Working hours / h

A

15

4

B

8

10

C

6

5

D

12

7

total

41

26

[0097] . Based on discrete quantum particle swarm algorithm, the scheduling method of bearing processing assembly line is as follows:

[0098] 1) Read in the process operation time of bearing processing as a known condition:

[0099] bearing in the machine The processing time o...

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Abstract

The invention discloses a method for scheduling a machine part processing line by adopting the discrete quantum particle swarm optimization, comprising the following steps: reading in the machine part processing process operation time, initializing a particle swarm, calculating the adaptation value of each particle, updating the individual optimal position and the global optimal position of each particle, carrying out global search on the basis of the discrete quantum particle optimization, carrying out local search and drawing a machine part processing sequence Gantt chart according to a global optimal scheduling scheme. The method disclosed by the invention improves the limitation of the traditional quantum particle swarm optimization in the production scheduling field, overcomes the defects that the quantum particle swarm is easy to be subjected to local optimization and has the advantages of high optimizing precision and high optimizing speed. The method is used for scheduling the machine part processing line, can solve to obtain an optimal scheduling scheme in a shorter time and is easy and convenient to operate. The principle has wide range of application and can be popularized to the producing and processing field of the manufacturing industry, the process industry and the like.

Description

technical field [0001] The invention relates to a machine part processing pipeline scheduling method, in particular to a machine part processing pipeline scheduling method based on a discrete quantum particle swarm algorithm. Background technique [0002] Machine parts processing pipeline scheduling belongs to pipeline scheduling, which is the most widely studied and applied typical production scheduling problem. At the same time, it is a complex combinatorial optimization problem with many variables and strong NP-hardness. It is also the core content of production management. With the expansion of production scale, the optimization of pipeline scheduling problem plays an increasingly important role in improving resource utilization, so its research has important theoretical and engineering value. [0003] Research on Pipeline Scheduling Problem on a machine In the flow processing process of each workpiece, the processing order of each part on each machine is the same, ...

Claims

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Application Information

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IPC IPC(8): G05B19/418G06N3/00
CPCY02P90/02
Inventor 张建明毛婧敏谢磊
Owner ZHEJIANG UNIV
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