Two-stage inter-cell layout design for cellular manufacturing by using ant colony optimization algorithms

Bo Xing, Wen Jing Gao, Fulufhelo V. Nelwamondo, Kimberly Battle, Tshilidzi Marwala

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

6 Citations (Scopus)

Abstract

Facility layout planning plays an important role in the manufacturing process and seriously impacts a company's profitability. A well-planned layout can significantly reduce the total material handling cost. The purpose of this paper is to develop a two-stage inter-cell layout optimization approach by using one of the popular meta-heuristics - the Ant Colony Optimization algorithm. At the first stage, the cells are formed based on the part-machine clustering results obtained through the ant system algorithm. In other words, we get the initial inter-cell layout after this stage. The work at the second stage uses a hybrid ant system algorithm to improve the solution obtained at previous stage. Different performance measures are also employed in this paper to evaluate the results.

Original languageEnglish
Title of host publicationAdvances in Swarm Intelligence - First International Conference, ICSI 2010, Proceedings
Pages281-289
Number of pages9
EditionPART 1
DOIs
Publication statusPublished - 2010
Event1st International Conference on Advances in Swarm Intelligence, ICSI 2010 - Beijing, China
Duration: 12 Jun 201015 Jun 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume6145 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference1st International Conference on Advances in Swarm Intelligence, ICSI 2010
Country/TerritoryChina
CityBeijing
Period12/06/1015/06/10

Keywords

  • ant colony optimization (ACO)
  • cell formation (CF)
  • cellular manufacturing (CM)
  • inter-cell layout (ICL)
  • material handling cost
  • quadratic assignment problem (QAP)

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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