Ant colony optimization for job shop scheduling

Research output: Contribution to conferencePaperpeer-review

5 Scopus citations

Abstract

A max-min ant colony optimization algorithm in the hyper-cube framework (MMHF) is developed to solve the jobshop scheduling problem with the objective of minimizing makespan. In MMHF, pheromone trail is limited to a fixed interval and the initial pheromone value becomes the mid-value of this interval. At every iteration, MMHF generates a schedule considering processing times along with the pheromone values. Pheromone values are iteratively adjusted through pheromone updating rules. When improved schedules cannot be generated in a given number of iterations, the pheromone trail is reinitialized with the initial pheromone value. In order to improve generated schedules by MMHF, a neighborhood search algorithm is used.

Original languageEnglish (US)
Pages1433-1438
Number of pages6
StatePublished - Dec 1 2008
EventIIE Annual Conference and Expo 2008 - Vancouver, BC, Canada
Duration: May 17 2008May 21 2008

Other

OtherIIE Annual Conference and Expo 2008
Country/TerritoryCanada
CityVancouver, BC
Period5/17/085/21/08

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Software
  • Industrial and Manufacturing Engineering

Fingerprint

Dive into the research topics of 'Ant colony optimization for job shop scheduling'. Together they form a unique fingerprint.

Cite this