Adapting genetic algorithm and tabu search approaches for unidirectional AGV flowpath design problems

Yoon Ho Seo, Chiung Moon, Young Hoon Moon, Taioun Kim, Sung Shick Kim

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

1 Citation (Scopus)

Abstract

In this paper we suggest an evolutionary computational approach by applying a combination of a genetic algorithm and a tabu search to obtain a good solution for relatively large unidirectional automated guided vehicle flowpath design problems. Unidirectional flowpaths are used to lessen the traffic control loads for large fleets of vehicles and to increase the efficiency in use of space. The flow path design is one of the most important steps in efficient vehicle systems design. We use an genetic algorithm to obtain partially directed networks, which are then completed and afterwards improved by a tabu search. A set of computational experiments is conducted to show the efficiency of the proposed solution procedure and the results are reported.

Original languageEnglish
Title of host publication2008 IEEE Congress on Evolutionary Computation, CEC 2008
Pages3621-3625
Number of pages5
DOIs
Publication statusPublished - 2008 Nov 14
Event2008 IEEE Congress on Evolutionary Computation, CEC 2008 - Hong Kong, China
Duration: 2008 Jun 12008 Jun 6

Other

Other2008 IEEE Congress on Evolutionary Computation, CEC 2008
CountryChina
CityHong Kong
Period08/6/108/6/6

    Fingerprint

Keywords

  • Genetic algorithm
  • Tabu search
  • Unidirectional flowpath design

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Theoretical Computer Science

Cite this

Seo, Y. H., Moon, C., Moon, Y. H., Kim, T., & Kim, S. S. (2008). Adapting genetic algorithm and tabu search approaches for unidirectional AGV flowpath design problems. In 2008 IEEE Congress on Evolutionary Computation, CEC 2008 (pp. 3621-3625). [4631288] https://doi.org/10.1109/CEC.2008.4631288