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Allocation search methods for a generalized class of location-allocation problems

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  • Bischoff, Martin
  • Dächert, Kerstin
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    Abstract

    We consider a generalized class of location-allocation problems, in which N new facilities are to be located in the plane with respect to M objects. Each object is associated with a convex cost function, specifying the expenses for serving the object from any location in the plane. For the resulting multi-dimensional mixed-integer optimization problem, we compare various traditional and new search methods. In particular, we apply multi-start, (variable) neighborhood search, tabu search, simulated annealing, an evolutionary algorithm and an ant colony optimization algorithm. They all have in common that they use the well-known alternate location and allocation algorithm [Cooper, L., 1964. Heuristic methods for location-allocation problems. SIAM Review 6, 37-53] as core local search function. We intend to impart a generalized view on these randomized search methods and also examine the efficiency of the different search strategies in solving the multi-connection location-allocation problem, a relatively new instance of the generalized class of location-allocation problems. Computational results show that the most crucial feature of the heuristics is the ability to combine a diversified search over the whole solution space with an intensified search near the best-known solution.

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    Bibliographic Info

    Article provided by Elsevier in its journal European Journal of Operational Research.

    Volume (Year): 192 (2009)
    Issue (Month): 3 (February)
    Pages: 793-807

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    Handle: RePEc:eee:ejores:v:192:y:2009:i:3:p:793-807

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    Web page: http://www.elsevier.com/locate/eor

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    Keywords: Meta-heuristics Location Mixed-integer optimization Randomized search Location-allocation;

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    1. Bischoff, M. & Klamroth, K., 2007. "An efficient solution method for Weber problems with barriers based on genetic algorithms," European Journal of Operational Research, Elsevier, vol. 177(1), pages 22-41, February.
    2. Rosing, K. E., 1992. "An optimal method for solving the (generalized) multi-Weber problem," European Journal of Operational Research, Elsevier, vol. 58(3), pages 414-426, May.
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