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Biological Clustering Method for Logistic Place Decision Making

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Knowledge-Based Intelligent Information and Engineering Systems (KES 2008)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5179))

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.

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Author information

Authors and Affiliations

  1. Graduate School of Information, Production and Systems, Waseda University, 2-7, Hibikino, Wakamatsu-Ku, Kitakyushu-Shi, Fukuoka-Ken, 808-0135, Japan

    Rohani Binti Abu Bakar & Junzo Watada

Authors
  1. Rohani Binti Abu Bakar
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  2. Junzo Watada
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Editor information

Ignac Lovrek Robert J. Howlett Lakhmi C. Jain

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© 2008 Springer-Verlag Berlin Heidelberg

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Abu Bakar, R.B., Watada, J. (2008). Biological Clustering Method for Logistic Place Decision Making. In: Lovrek, I., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2008. Lecture Notes in Computer Science(), vol 5179. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85567-5_18

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  • DOI: https://doi.org/10.1007/978-3-540-85567-5_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-85566-8

  • Online ISBN: 978-3-540-85567-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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