Multiobjective job shop scheduling using genetic algorithm with cyclic fitness assignment

Tsung Che Chiang*, Li Chen Fu

*Corresponding author for this work

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
Externally publishedYes
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
Country/TerritoryCanada
CityVancouver, BC
Period2006/07/162006/07/21

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Theoretical Computer Science

Fingerprint

Dive into the research topics of 'Multiobjective job shop scheduling using genetic algorithm with cyclic fitness assignment'. Together they form a unique fingerprint.

Cite this