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An approach for solving a fuzzy multiobjective programming problem

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  • Luhandjula, M.K.
  • Rangoaga, M.J.

Abstract

In this paper we present a new approach, based on the Nearest Interval Approximation Operator, for dealing with a multiobjective programming problem with fuzzy-valued objective functions.

Suggested Citation

  • Luhandjula, M.K. & Rangoaga, M.J., 2014. "An approach for solving a fuzzy multiobjective programming problem," European Journal of Operational Research, Elsevier, vol. 232(2), pages 249-255.
    • Handle: RePEc:eee:ejores:v:232:y:2014:i:2:p:249-255
    DOI: 10.1016/j.ejor.2013.05.040
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    References listed on IDEAS

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    1. Ishibuchi, Hisao & Tanaka, Hideo, 1990. "Multiobjective programming in optimization of the interval objective function," European Journal of Operational Research, Elsevier, vol. 48(2), pages 219-225, September.
    2. Bravo, Mila & Gonzalez, Ignacio, 2009. "Applying stochastic goal programming: A case study on water use planning," European Journal of Operational Research, Elsevier, vol. 196(3), pages 1123-1129, August.
    3. Luciano Stefanini & Barnabas Bede, 2008. "Generalized Hukuhara Differentiability of Interval-valued Functions and Interval Differential Equations," Working Papers 0803, University of Urbino Carlo Bo, Department of Economics, Society & Politics - Scientific Committee - L. Stefanini & G. Travaglini, revised 2008.
    4. Gerd Infanger (ed.), 2011. "Stochastic Programming," International Series in Operations Research and Management Science, Springer, number 978-1-4419-1642-6, December.
    5. Sakawa, Masatoshi & Yauchi, Katsuhiro, 1999. "An interactive fuzzy satisficing method for multiobjective nonconvex programming problems through floating point genetic algorithms," European Journal of Operational Research, Elsevier, vol. 117(1), pages 113-124, August.
    6. Chang, Ni-Bin & Wen, C.G. & Chen, Y.L., 1997. "A fuzzy multi-objective programming approach for optimal management of the reservoir watershed," European Journal of Operational Research, Elsevier, vol. 99(2), pages 289-302, June.
    7. Canto, Salvador Perez, 2008. "Application of Benders' decomposition to power plant preventive maintenance scheduling," European Journal of Operational Research, Elsevier, vol. 184(2), pages 759-777, January.
    8. Wu, Hsien-Chung, 2007. "The Karush-Kuhn-Tucker optimality conditions in an optimization problem with interval-valued objective function," European Journal of Operational Research, Elsevier, vol. 176(1), pages 46-59, January.
    9. Luhandjula, M.K. & Joubert, J.W., 2010. "On some optimisation models in a fuzzy-stochastic environment," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1433-1441, December.
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    Cited by:

    1. Vishnu Singh & Shiv Prasad Yadav & Sujeet Kumar Singh, 2021. "Duality theory in Atanassov’s intuitionistic fuzzy mathematical programming problems: Optimistic, pessimistic and mixed approaches," Annals of Operations Research, Springer, vol. 296(1), pages 667-706, January.
    2. Beatriz Hernández-Jiménez & Gabriel Ruiz-Garzón & Antonio Beato-Moreno & Rafaela Osuna-Gómez, 2021. "A Better Approach for Solving a Fuzzy Multiobjective Programming Problem by Level Sets," Mathematics, MDPI, vol. 9(9), pages 1-14, April.
    3. Reza Ghanbari & Khatere Ghorbani-Moghadam & Nezam Mahdavi-Amiri, 2021. "A time variant multi-objective particle swarm optimization algorithm for solving fuzzy number linear programming problems using modified Kerre’s method," OPSEARCH, Springer;Operational Research Society of India, vol. 58(2), pages 403-424, June.
    4. Fabiola Roxana Villanueva & Valeriano Antunes Oliveira, 2022. "Necessary Optimality Conditions for Interval Optimization Problems with Functional and Abstract Constraints," Journal of Optimization Theory and Applications, Springer, vol. 194(3), pages 896-923, September.

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