Scheduling multi-processor tasks with resource and timing constraints using genetic algorithm

Shu Chen Cheng, Yueh Min Huang

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

11 Citations (Scopus)

Abstract

The job-shop scheduling problems have been categorized as NP-complete problems. The exponential growth of the time required to obtain an optimal solution makes the exhaustive search for global optimal schedules very difficult or even impossible. Recently, genetic algorithms have shown the feasibility to solve the job-shop scheduling problems. However, a pure GA-based approach tends to generate illegal schedules due to the crossover and the mutation operators, it is often the case that the gene expression or the genetic operators need to be specially designed to fit the problem domain or some other schemes may be combined to solve the scheduling problems. This paper presents a GA-based approach with a feasible energy, function to generate good-quality schedules. In our work, we design an easy-understood genotype to generate legal schedules and the proposed approach converges rapidly.

Original languageEnglish
Title of host publicationProceedings - 2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation
Subtitle of host publicationComputational Intelligence in Robotics and Automation for the New Millennium
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages624-629
Number of pages6
ISBN (Electronic)0780378660
DOIs
Publication statusPublished - 2003 Jan 1
Event2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2003 - Kobe, Japan
Duration: 2003 Jul 162003 Jul 20

Publication series

NameProceedings of IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA
Volume2

Other

Other2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2003
CountryJapan
CityKobe
Period03-07-1603-07-20

All Science Journal Classification (ASJC) codes

  • Computational Mathematics

Fingerprint Dive into the research topics of 'Scheduling multi-processor tasks with resource and timing constraints using genetic algorithm'. Together they form a unique fingerprint.

Cite this