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An interactive algorithm to find the most preferred solution of multi-objective integer programs

Author

Listed:
  • Banu Lokman

    (TED University)

  • Murat Köksalan

    (Middle East Technical University)

  • Pekka J. Korhonen

    (Aalto University)

  • Jyrki Wallenius

    (Aalto University)

Abstract

In this paper, we develop an interactive algorithm that finds the most preferred solution of a decision maker (DM) for multi-objective integer programming problems. We assume that the DM’s preferences are consistent with a quasiconcave value function unknown to us. Based on the properties of quasiconcave value functions and pairwise preference information obtained from the DM, we generate constraints to restrict the implied inferior regions. The algorithm continues iteratively and guarantees to find the most preferred solution for integer programs. We test the performance of the algorithm on multi-objective assignment, knapsack, and shortest path problems and show that it works well.

Suggested Citation

  • Banu Lokman & Murat Köksalan & Pekka J. Korhonen & Jyrki Wallenius, 2016. "An interactive algorithm to find the most preferred solution of multi-objective integer programs," Annals of Operations Research, Springer, vol. 245(1), pages 67-95, October.
    • Handle: RePEc:spr:annopr:v:245:y:2016:i:1:d:10.1007_s10479-014-1545-2
    DOI: 10.1007/s10479-014-1545-2
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    References listed on IDEAS

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    Cited by:

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    2. Bashir Bashir & Özlem Karsu, 2022. "Solution approaches for equitable multiobjective integer programming problems," Annals of Operations Research, Springer, vol. 311(2), pages 967-995, April.
    3. Selin Özpeynirci & Özgür Özpeynirci & Vincent Mousseau, 2021. "An interactive algorithm for resource allocation with balance concerns," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(4), pages 983-1005, December.
    4. Wassila Drici & Fatma Zohra Ouail & Mustapha Moulaï, 2018. "Optimizing a linear fractional function over the integer efficient set," Annals of Operations Research, Springer, vol. 267(1), pages 135-151, August.
    5. Karakaya, G. & Köksalan, M. & Ahipaşaoğlu, S.D., 2018. "Interactive algorithms for a broad underlying family of preference functions," European Journal of Operational Research, Elsevier, vol. 265(1), pages 248-262.
    6. Özlem Karsu & Hale Erkan, 2020. "Balance in resource allocation problems: a changing reference approach," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 42(1), pages 297-326, March.
    7. Karakaya, G. & Köksalan, M., 2023. "Finding preferred solutions under weighted Tchebycheff preference functions for multi-objective integer programs," European Journal of Operational Research, Elsevier, vol. 308(1), pages 215-228.
    8. Karakaya, G. & Köksalan, M., 2021. "Evaluating solutions and solution sets under multiple objectives," European Journal of Operational Research, Elsevier, vol. 294(1), pages 16-28.
    9. Nasim Nasrabadi & Akram Dehnokhalaji & Pekka Korhonen & Jyrki Wallenius, 2019. "Using convex preference cones in multiple criteria decision making and related fields," Journal of Business Economics, Springer, vol. 89(6), pages 699-717, August.

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