Advertisement

Improving the Efficiency of Branch and Bound Algorithms for the Simple Plant Location Problem

  • Boris Goldengorin
  • Diptesh Ghosh
  • Gerard Sierksma
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2141)

Abstract

The simple plant location problem is a well-studied problem in combinatorial optimization. It is one of deciding where to locate a set of plants so that a set of clients can be supplied by them at the minimum cost. This problem often appears as a subproblem in other combinatorial problems. Several branch and bound techniques have been developed to solve this problem. In this paper we present some techniques that enhance the performance of branch and bound algorithms. Computational experiments show that the new algorithms thus obtained generate less than 60% of the number of subproblems generated by branch and bound algorithms, and in certain cases require less than 10% of the execution times required by conventional branch and bound algorithms.

Keywords

Execution Time Problem Instance Transportation Cost Partial Solution Average Execution Time 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    J. E. Beasley. OR-Library, http://mscmga.ms.ic.ac.uk/info.html
  2. 2.
    V. L. Beresnev. On a Problem of Mathematical Standardization Theory. Upravliajemyje Sistemy 11, 43–54, 1973 (in Russian).Google Scholar
  3. 3.
    V. L. Beresnev, E. Kh. Gimadi, V. T. Dementyev. Extremal Standardization Problems, Novosibirsk, Nauka, 1978 (in Russian).Google Scholar
  4. 4.
    N. Christofides. Graph Theory: An Algorithmic Approach. Academic Press Inc. Ltd., London, 1975.zbMATHGoogle Scholar
  5. 5.
    G. Cornuejols, G. L. Nemhauser, and L. A. Wolsey. The Uncapacitated Facility Location Problem. Ch.3, Discrete Location Theory, R. L. Francis and P. B. Mirchandani (eds.), Wiley-Interscience, New York, 1990.Google Scholar
  6. 6.
    P. M. Dearing, P. L. Hammer, B. Simeone, Boolean and Graph Theoretic Formulations of the Simple Plant Location Problem. Transportation Science 26, 138–148, 1992.zbMATHCrossRefGoogle Scholar
  7. 7.
    B. Goldengorin. Requirements of Standards: Optimization Models and Algorithms. ROR, Hoogezand, The Netherlands, 1995.Google Scholar
  8. 8.
    B. Goldengorin, D. Ghosh, and G. Sierksma. Equivalent Instances of the Simple Plant Location Problem. SOM Research Report-00A54, 2000.Google Scholar
  9. 9.
    P. L. Hammer. Plant Location — A Pseudo-Boolean Approach. Israel Journal of Technology 6, 330–332, 1968.Google Scholar
  10. 10.
    P. C. Jones, T. J. Lowe, G. Muller, N. Xu, Y. Ye and J. L. Zydiak. Specially Structured Uncapacitated Facility Location Problems. Operations Research 43, 661–669, 1995.zbMATHCrossRefMathSciNetGoogle Scholar
  11. 11.
    D. W. Pentico. The Discrete Two-Dimensional Assortment Problem. Operations Research 36, 324–332, 1988.zbMATHCrossRefMathSciNetGoogle Scholar
  12. 12.
    C. S. Revelle and G. Laporte. The Plant Location Problem: New Models and Research Prospects. Operations Research 44, 864–874, 1996.zbMATHCrossRefGoogle Scholar
  13. 13.
    A. Tripathy, Süral, and Y. Gerchak. Multidimensional Assortment Problem with an Application. Networks 33, 239–245, 1999.zbMATHCrossRefMathSciNetGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Boris Goldengorin
    • 1
  • Diptesh Ghosh
    • 1
  • Gerard Sierksma
    • 1
  1. 1.Faculty of Economic SciencesUniversity of GroningenGroningenThe Netherlands

Personalised recommendations