Multiobjective job shop scheduling using genetic algorithm with cyclic fitness assignment

Tsung-Che Chiang, Li Chen Fu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

A job shop scheduling problem with total tardiness and the maximum tardiness as objectives is addressed. We solve it by a rule-coded genetic algorithm. Characteristics of three existing fitness assignment mechanisms are identified and then combined through the proposed cyclic fitness assignment mechanism. Experiments are conducted on a public benchmark problem set, and the results show that the proposed algorithm outperforms the existing ones.

Original languageEnglish
Title of host publication2006 IEEE Congress on Evolutionary Computation, CEC 2006
Pages3266-3273
Number of pages8
Publication statusPublished - 2006 Dec 1
Event2006 IEEE Congress on Evolutionary Computation, CEC 2006 - Vancouver, BC, Canada
Duration: 2006 Jul 162006 Jul 21

Publication series

Name2006 IEEE Congress on Evolutionary Computation, CEC 2006

Other

Other2006 IEEE Congress on Evolutionary Computation, CEC 2006
CountryCanada
CityVancouver, BC
Period06/7/1606/7/21

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ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Theoretical Computer Science

Cite this

Chiang, T-C., & Fu, L. C. (2006). Multiobjective job shop scheduling using genetic algorithm with cyclic fitness assignment. In 2006 IEEE Congress on Evolutionary Computation, CEC 2006 (pp. 3266-3273). [1688724] (2006 IEEE Congress on Evolutionary Computation, CEC 2006).