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Biobjective robust optimization over the efficient set for Pareto set reduction

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  • Jornada, Daniel
  • Leon, V. Jorge

Abstract

This paper presents a biobjective robust optimization formulation for identifying robust solutions from a given Pareto set. The objectives consider both solution and model robustness when the exact values of the selected solution are affected by uncertainty. The problem is formulated equivalently as a model with uncertainty on the constraint parameters and objective function coefficients. Structural properties and a solution algorithm are developed for the case of multiobjective linear programs. The algorithm is based on facial decomposition; each subproblem is a biobjective linear program and is related to an efficient face of the multiobjective program. The resulting Pareto set reduction methodology allows the handling of continuous and discrete Pareto sets, and can be generalized to consider criteria other than robustness. The use of secondary criteria to further break ties among the many efficient solutions provides opportunities for additional trade-off analysis in the space of the secondary criteria. Examples illustrate the algorithm and characteristics of solutions obtained.

Suggested Citation

  • Jornada, Daniel & Leon, V. Jorge, 2016. "Biobjective robust optimization over the efficient set for Pareto set reduction," European Journal of Operational Research, Elsevier, vol. 252(2), pages 573-586.
  • Handle: RePEc:eee:ejores:v:252:y:2016:i:2:p:573-586
    DOI: 10.1016/j.ejor.2016.01.017
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    1. Horst, Reiner & Thoai, Nguyen V., 1999. "Maximizing a concave function over the efficient or weakly-efficient set," European Journal of Operational Research, Elsevier, vol. 117(2), pages 239-252, September.
    2. Dimitris Bertsimas & Melvyn Sim, 2004. "The Price of Robustness," Operations Research, INFORMS, vol. 52(1), pages 35-53, February.
    3. Mavrotas, George & Pechak, Olena & Siskos, Eleftherios & Doukas, Haris & Psarras, John, 2015. "Robustness analysis in Multi-Objective Mathematical Programming using Monte Carlo simulation," European Journal of Operational Research, Elsevier, vol. 240(1), pages 193-201.
    4. Alexander Engau & Margaret M. Wiecek, 2008. "Interactive Coordination of Objective Decompositions in Multiobjective Programming," Management Science, INFORMS, vol. 54(7), pages 1350-1363, July.
    5. Mavrotas, George & Figueira, José Rui & Siskos, Eleftherios, 2015. "Robustness analysis methodology for multi-objective combinatorial optimization problems and application to project selection," Omega, Elsevier, vol. 52(C), pages 142-155.
    6. Serpil Sayin, 2000. "Optimizing Over the Efficient Set Using a Top-Down Search of Faces," Operations Research, INFORMS, vol. 48(1), pages 65-72, February.
    7. Goberna, M.A. & Jeyakumar, V. & Li, G. & Vicente-Pérez, J., 2015. "Robust solutions to multi-objective linear programs with uncertain data," European Journal of Operational Research, Elsevier, vol. 242(3), pages 730-743.
    8. Ehrgott, Matthias & Tenfelde-Podehl, Dagmar, 2003. "Computation of ideal and Nadir values and implications for their use in MCDM methods," European Journal of Operational Research, Elsevier, vol. 151(1), pages 119-139, November.
    9. Ehrgott, Matthias & Ide, Jonas & Schöbel, Anita, 2014. "Minmax robustness for multi-objective optimization problems," European Journal of Operational Research, Elsevier, vol. 239(1), pages 17-31.
    10. Dimitris Bertsimas & David B. Brown, 2009. "Constructing Uncertainty Sets for Robust Linear Optimization," Operations Research, INFORMS, vol. 57(6), pages 1483-1495, December.
    11. Jorge, Jesús M., 2009. "An algorithm for optimizing a linear function over an integer efficient set," European Journal of Operational Research, Elsevier, vol. 195(1), pages 98-103, May.
    12. Luque, Mariano & Ruiz, Francisco & Steuer, Ralph E., 2010. "Modified interactive Chebyshev algorithm (MICA) for convex multiobjective programming," European Journal of Operational Research, Elsevier, vol. 204(3), pages 557-564, August.
    13. T. J. Lowe & J.-F. Thisse & J. E. Ward & R. E. Wendell, 1984. "On Efficient Solutions to Multiple Objective Mathematical Programs," Management Science, INFORMS, vol. 30(11), pages 1346-1349, November.
    14. Alves, Maria Joao & Climaco, Joao, 2007. "A review of interactive methods for multiobjective integer and mixed-integer programming," European Journal of Operational Research, Elsevier, vol. 180(1), pages 99-115, July.
    15. Ben-Tal, A. & den Hertog, D., 2011. "Immunizing Conic Quadratic Optimization Problems Against Implementation Errors," Discussion Paper 2011-060, Tilburg University, Center for Economic Research.
    16. John M. Mulvey & Robert J. Vanderbei & Stavros A. Zenios, 1995. "Robust Optimization of Large-Scale Systems," Operations Research, INFORMS, vol. 43(2), pages 264-281, April.
    17. Alves, Maria João & Costa, João Paulo, 2009. "An exact method for computing the nadir values in multiple objective linear programming," European Journal of Operational Research, Elsevier, vol. 198(2), pages 637-646, October.
    18. Ben-Tal, A. & den Hertog, D., 2011. "Immunizing Conic Quadratic Optimization Problems Against Implementation Errors," Other publications TiSEM 9f3fba48-8501-4ec8-9241-5, Tilburg University, School of Economics and Management.
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