On the analysis of crossover schemes for Genetic Algorithms applied to the job shop scheduling problem

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Abstract

In this paper we perform a detailed analysis of crossover operators and solution decoding schemes for Genetic Algorithms (GAs) applied to the Job Shop Scheduling Problem (JSSP). Based on the job sequence matrix encoding we investigate in how far existing crossover operators are able to preserve characteristics from parent individuals. Assuming that individuals have to represent active solutions, repair techniques (forcing) have to be applied during the decoding process. We study the effects of different decoding schemes and forcing strategies and point out to what extent they cause disruption of crossover results. Finally we present computational results for selected benchmark problems.

Original languageEnglish
Title of host publicationWMSCI 2005 - The 9th World Multi-Conference on Systemics, Cybernetics and Informatics, Proceedings
PublisherInternational Institute of Informatics and Systemics
Pages236-241
Number of pages6
ISBN (Print)9806560582, 9789806560581
Publication statusPublished - 2005
Event9th World Multi-Conference on Systemics, Cybernetics and Informatics, WMSCI 2005 - Orlando, FL, United States
Duration: 10 Jul 200513 Jul 2005

Publication series

NameWMSCI 2005 - The 9th World Multi-Conference on Systemics, Cybernetics and Informatics, Proceedings
Volume6

Conference

Conference9th World Multi-Conference on Systemics, Cybernetics and Informatics, WMSCI 2005
CountryUnited States
CityOrlando, FL
Period10.07.200513.07.2005

Keywords

  • Crossover
  • Forcing
  • Genetic Algorithms
  • Job sequence matrix
  • Job shop scheduling
  • Solution decoding

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