Can ant algorithms make automated guided vehicle system more intelligent? A viewpoint from manufacturing environment

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

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

12 Citations (Scopus)

Abstract

In manufacturing environment, an automated guided vehicle (AGV) system is composed of a set of driver-less vehicles that transport goods and materials between distinct workstations and storage locations of shops. In soft computing area, ant algorithms are a series of population-based approaches inspired by various behaviors of real ant colonies. During the last two decades, ant algorithms have achieved a great success in solving many combinatorial optimization problems. In this article we make an attempt to study the feasibility of applying ant algorithms to different problems encountered in AGV system design and control. By making use of ant algorithms' strengths, we hope to provide the readers with alternative options for solving conventional AGV system design and control problems, as well as to point out some new directions for AGV system research.

Original languageEnglish
Title of host publication2010 IEEE International Conference on Systems, Man and Cybernetics, SMC 2010
Pages3226-3234
Number of pages9
DOIs
Publication statusPublished - 2010
Event2010 IEEE International Conference on Systems, Man and Cybernetics, SMC 2010 - Istanbul, Turkey
Duration: 10 Oct 201013 Oct 2010

Publication series

NameConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
ISSN (Print)1062-922X

Conference

Conference2010 IEEE International Conference on Systems, Man and Cybernetics, SMC 2010
Country/TerritoryTurkey
CityIstanbul
Period10/10/1013/10/10

Keywords

  • Ant algorithms
  • Automated guided vehicle
  • Cooperative transportation
  • Dispatching
  • Guide path
  • Loading unit
  • Mobile ad hoc network
  • Routing
  • Traffic control

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Human-Computer Interaction

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