Multi-agent based genetic algorithm for JSSP

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14 Scopus citations

Abstract

A novel multi-agent based on Genetic Algorithm (GA) is proposed to solve Job-Shop Scheduling Problem (JSSP). This algorithm not only can accelerate the creation of initial population and the selection of evaluation population, but also can control the processing of selection, crossover and mutation in an intelligent way. Job-shop benchmarks are used to evaluate the efficiency and performance of the proposed algorithm. The experimental result shows it has better optimal performance.

Original languageEnglish
Title of host publicationProceedings of 2004 International Conference on Machine Learning and Cybernetics
Pages267-270
Number of pages4
StatePublished - 2004
EventProceedings of 2004 International Conference on Machine Learning and Cybernetics - Shanghai, China
Duration: 26 Aug 200429 Aug 2004

Publication series

NameProceedings of 2004 International Conference on Machine Learning and Cybernetics
Volume1

Conference

ConferenceProceedings of 2004 International Conference on Machine Learning and Cybernetics
Country/TerritoryChina
CityShanghai
Period26/08/0429/08/04

Keywords

  • Genetic algorithms
  • Job-shop Scheduling Problem (JSSP)
  • Multi-agent

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