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Heuristic approaches for biobjective mixed 0–1 integer linear programming problems

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  • Soylu, Banu

Abstract

In this study, biobjective mixed 0–1 integer linear programming problems are considered and two heuristic approaches are presented to find the Pareto frontier of these problems. The first heuristic is a variant of the variable neighborhood search and explores the k-neighbors of a feasible solution (in terms of binary variables) to find the extreme supported Pareto points. The second heuristic is adapted from the local branching method, which is well-known in single objective mixed 0–1 integer linear programming. Finally, an algorithm is proposed to find Pareto segments of outcome line segments of these heuristics. A computational analysis is performed by using some test problems from the literature and the results are presented.

Suggested Citation

  • Soylu, Banu, 2015. "Heuristic approaches for biobjective mixed 0–1 integer linear programming problems," European Journal of Operational Research, Elsevier, vol. 245(3), pages 690-703.
  • Handle: RePEc:eee:ejores:v:245:y:2015:i:3:p:690-703
    DOI: 10.1016/j.ejor.2015.04.010
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    Cited by:

    1. Yıldız, Gazi Bilal & Soylu, Banu, 2019. "A multiobjective post-sales guarantee and repair services network design problem," International Journal of Production Economics, Elsevier, vol. 216(C), pages 305-320.
    2. Nathan Adelgren & Akshay Gupte, 2022. "Branch-and-Bound for Biobjective Mixed-Integer Linear Programming," INFORMS Journal on Computing, INFORMS, vol. 34(2), pages 909-933, March.
    3. Aritra Pal & Hadi Charkhgard, 2019. "A Feasibility Pump and Local Search Based Heuristic for Bi-Objective Pure Integer Linear Programming," INFORMS Journal on Computing, INFORMS, vol. 31(1), pages 115-133, February.
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    5. Soylu, Banu & Katip, Hatice, 2019. "A multiobjective hub-airport location problem for an airline network design," European Journal of Operational Research, Elsevier, vol. 277(2), pages 412-425.
    6. Konur, Dinçer & Campbell, James F. & Monfared, Sepideh A., 2017. "Economic and environmental considerations in a stochastic inventory control model with order splitting under different delivery schedules among suppliers," Omega, Elsevier, vol. 71(C), pages 46-65.
    7. Lakmali Weerasena & Aniekan Ebiefung & Anthony Skjellum, 2022. "Design of a heuristic algorithm for the generalized multi-objective set covering problem," Computational Optimization and Applications, Springer, vol. 82(3), pages 717-751, July.
    8. Lakmali Weerasena & Margaret M. Wiecek & Banu Soylu, 2017. "An algorithm for approximating the Pareto set of the multiobjective set covering problem," Annals of Operations Research, Springer, vol. 248(1), pages 493-514, January.
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    10. Daniel Jornada & V. Jorge Leon, 2020. "Filtering Algorithms for Biobjective Mixed Binary Linear Optimization Problems with a Multiple-Choice Constraint," INFORMS Journal on Computing, INFORMS, vol. 32(1), pages 57-73, January.

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