Biological clustering method for logistic place decision making

Rohani Binti Abu Bakar, Junzo Watada

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

    6 Citations (Scopus)

    Abstract

    One of the main tasks in supply chain network is to identify the determination of logistic location. The main factors could influence the selections are costs and profits for the company itself. Most appropriate place is urgently essentials in today business world to ensure the company could be more competitive then other competitors in the industry. A lot of considerations should be taken during selecting a location to build a logistic place to serve other retailers city effectively. Currently, there are so many algorithms based on different approaches are proposed by other researchers. Thus, this paper intends to propose DNA computing approach to solve the problem. In this study, a cluster-based approach is employ when all cities are grouped before we choose a right city as distribution center. A case study is presented at the end of this paper to illustrate how the proposed technique works.

    Original languageEnglish
    Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Pages136-143
    Number of pages8
    Volume5179 LNAI
    EditionPART 3
    DOIs
    Publication statusPublished - 2008
    Event12th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2008 - Zagreb
    Duration: 2008 Sep 32008 Sep 5

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    NumberPART 3
    Volume5179 LNAI
    ISSN (Print)03029743
    ISSN (Electronic)16113349

    Other

    Other12th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2008
    CityZagreb
    Period08/9/308/9/5

    Keywords

    • Biologically inspired computing
    • Cluster-based
    • Determination
    • DNA computing
    • Logistic location
    • Logistic problem

    ASJC Scopus subject areas

    • Computer Science(all)
    • Theoretical Computer Science

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  • Cite this

    Bakar, R. B. A., & Watada, J. (2008). Biological clustering method for logistic place decision making. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (PART 3 ed., Vol. 5179 LNAI, pp. 136-143). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5179 LNAI, No. PART 3). https://doi.org/10.1007/978-3-540-85567-5-18