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Capacitated Vehicle Routing Problem with Fuzzy Demand

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Fuzzy Sets Based Heuristics for Optimization

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 126))

Abstract

The capacitated vehicle routing problem with fuzzy demand is considered. Since customers’ demand is not precisely known in advance, but is given as uncertain quantities, i.e. as fuzzy numbers, a recommended route may not meet each demand for capacity reasons. Route failure will result in losing the part of demand which could not be satisfied. Consequently, the possibility, or indeed necessity, to satisfy all customers’ demand has to be high. Optimization should additionally consider several conflicting objectives, e.g. minimizing total travel costs as well as maximizing sales.

In this article, a fuzzy multi-criteria modeling approach, based on a mixed integer linear mathematical programming model, is presented. In order to solve even larger problems, the established savings heuristic for the classical vehicle routing problem is modified appropriately with regard to fuzzy demand and multi-criteria optimization. A compromise solution is determined interactively by the decision maker, who adjusts the degree of satisfaction with the different goals. The solution method is demonstrated in a 75-customer example.

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Author information

Authors and Affiliations

  1. Faculty of Economics and Business Administration, Ruhr-University Bochum, Universitätsstr. 150, D-44780, Bochum, Germany

    Brigitte Werners & Michael Drawe

Authors
  1. Brigitte Werners
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  2. Michael Drawe
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Editor information

Editors and Affiliations

  1. Dept. Computer Science and A.I., University of Granada, 18071, Granada, Spain

    José-Luis Verdegay

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© 2003 Springer-Verlag Berlin Heidelberg

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Werners, B., Drawe, M. (2003). Capacitated Vehicle Routing Problem with Fuzzy Demand. In: Verdegay, JL. (eds) Fuzzy Sets Based Heuristics for Optimization. Studies in Fuzziness and Soft Computing, vol 126. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-36461-0_21

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  • DOI: https://doi.org/10.1007/978-3-540-36461-0_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-05611-6

  • Online ISBN: 978-3-540-36461-0

  • eBook Packages: Springer Book Archive

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