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An Algorithm for Multiobjective Zero-One Linear Programming

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Author Info

  • Gülseren Kiziltan

    (Marmara Scientific and Industrial Research Institute, Kocaeli, Turkey)

  • Erkut Yucao\u{g}lu

    (Turkish Electrical Industries Corporation, Istanbul, Turkey)

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    Abstract

    A branch and bound algorithm is presented which is based on the extension of implicit enumeration techniques to multiobjective zero-one linear programming and which appears to be computationally quite efficient. Domination tests, aiming at identifying paths of the enumeration tree that lead to dominated solutions as high up the tree as possible, are developed. Some computational results are also given.

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    File URL: http://dx.doi.org/10.1287/mnsc.29.12.1444
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    Bibliographic Info

    Article provided by INFORMS in its journal Management Science.

    Volume (Year): 29 (1983)
    Issue (Month): 12 (December)
    Pages: 1444-1453

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    Handle: RePEc:inm:ormnsc:v:29:y:1983:i:12:p:1444-1453

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    Related research

    Keywords: programming: multiple criteria;

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    Cited by:
    1. Karaivanova, Jasmina & Korhonen, Pekka & Narula, Subhash & Wallenius, Jyrki & Vassilev, Vassil, 1995. "A reference direction approach to multiple objective integer linear programming," European Journal of Operational Research, Elsevier, vol. 81(1), pages 176-187, February.
    2. Sylva, John & Crema, Alejandro, 2004. "A method for finding the set of non-dominated vectors for multiple objective integer linear programs," European Journal of Operational Research, Elsevier, vol. 158(1), pages 46-55, October.
    3. Zhang, Cai Wen & Ong, Hoon Liong, 2004. "Solving the biobjective zero-one knapsack problem by an efficient LP-based heuristic," European Journal of Operational Research, Elsevier, vol. 159(3), pages 545-557, December.
    4. Skriver, Anders J. V. & Andersen, Kim Allan & Holmberg, Kaj, 2004. "Bicriteria network location (BNL) problems with criteria dependent lengths and minisum objectives," European Journal of Operational Research, Elsevier, vol. 156(3), pages 541-549, August.
    5. Liesiö, Juuso & Salo, Ahti, 2012. "Scenario-based portfolio selection of investment projects with incomplete probability and utility information," European Journal of Operational Research, Elsevier, vol. 217(1), pages 162-172.
    6. Nikolaos Argyris & José Figueira & Alec Morton, 2011. "Identifying preferred solutions to Multi-Objective Binary Optimisation problems, with an application to the Multi-Objective Knapsack Problem," Journal of Global Optimization, Springer, vol. 49(2), pages 213-235, February.
    7. Mavrotas, G. & Diakoulaki, D., 1998. "A branch and bound algorithm for mixed zero-one multiple objective linear programming," European Journal of Operational Research, Elsevier, vol. 107(3), pages 530-541, June.

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