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29808

Comparison of Particle SWARM Optimization, Genetic Algorithm and Max separable Technique for Machine Time Scheduling Problem

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Last updated: 22 Jan 2023

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Abstract

Abstract
In this paper we deal with a multi cycle machine time scheduling problem (MTSP) to find the best starting time for each machine in each cycle. We introduce an algorithm by using the particle SWARM optimization (PSO) and Genetic algorithm to solve the MTSP. A comparison between PSO, GA and max-separable technique will be introduced to find the best solution which is the best starting time respect to its time window for each machine in each cycle and respect to the set of precedence machines to minimize the penalty cost.

DOI

10.21608/icmep.2010.29808

Keywords

Machine Time Scheduling, Particle Swarm Optimization, Genetic Algorithm, Max-separable, Time Window

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El-sawy

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First Name

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Tharwat

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Volume

5

Article Issue

International Conference on Mathematics and Engineering Physics (ICMEP-5)

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5195

Issue Date

2010-05-01

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2019-04-08

Publish Date

2010-05-01

Page Start

1

Page End

10

Print ISSN

2636-431X

Online ISSN

2636-4328

Article File

ICMEP_Volume 5_Issue International Conference on Mathematics and Engineering Physics (ICMEP-5)_Pages 1-10.pdf

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https://icmep.journals.ekb.eg/article_29808.html

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https://icmep.journals.ekb.eg/service?article_code=29808

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830

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The International Conference on Mathematics and Engineering Physics

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https://icmep.journals.ekb.eg/

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Created At

22 Jan 2023