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

Yoonho Seo, Chiung Moon, Young Hoon Moon, Taioun Kim, Sung Shick Kim

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

    2 Citations (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
    Event2008 IEEE Congress on Evolutionary Computation, CEC 2008 - Hong Kong, China
    Duration: 2008 Jun 12008 Jun 6

    Publication series

    Name2008 IEEE Congress on Evolutionary Computation, CEC 2008

    Other

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

    Keywords

    • Genetic algorithm
    • Tabu search
    • Unidirectional flowpath design

    ASJC Scopus subject areas

    • Computational Theory and Mathematics
    • Theoretical Computer Science

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