Skip to main navigation Skip to search Skip to main content

A virus evolution genetic algorithm for scheduling problem with penalties of independent tasks on a single machine

  • School of Computer Science and Technology, Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Scheduling problem with penalties of independent tasks on a single machine is a NP-hard problem. In this paper, a scheduling problem of n tasks which have different ready times and due dates is given. With respect to this problem, a virus evolution genetic algorithm called SMSP-VEGA is developed. SMSP-VEGA is used to obtain the optimal scheduling sequences for the tasks so that the total tardy penalty costs are minimized. Different from GA, SMSP-VEGA has two types of operator: genetic operator and virus-infection operator. As the genetic operators can transfer evolutionary genes from parent to child generation and the virus-infection operators can spread evolutionary genes in the same generation, respectively, It can perform global search and local search in the same time. The schema theory is adopted to analyze the performance of SMSP-VEGA and the experimental results are also given. The theoretical analysis and experimental results show that the SMSP-VEGA outperforms the GA.

Original languageEnglish
Title of host publicationProceedings of the 2009 WRI Global Congress on Intelligent Systems, GCIS 2009
Pages574-578
Number of pages5
DOIs
StatePublished - 2009
Externally publishedYes
Event2009 WRI Global Congress on Intelligent Systems, GCIS 2009 - Xiamen, China
Duration: 19 May 200921 May 2009

Publication series

NameProceedings of the 2009 WRI Global Congress on Intelligent Systems, GCIS 2009
Volume1

Conference

Conference2009 WRI Global Congress on Intelligent Systems, GCIS 2009
Country/TerritoryChina
CityXiamen
Period19/05/0921/05/09

Keywords

  • Genetic algorithm
  • Independent tasks
  • Single machine scheduling
  • Tardy penalties
  • Virus evolution

Fingerprint

Dive into the research topics of 'A virus evolution genetic algorithm for scheduling problem with penalties of independent tasks on a single machine'. Together they form a unique fingerprint.

Cite this