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A satisficing method for fuzzy goal programming problems with different importance and priorities

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  • Hung-Wen Cheng

Abstract

For treating multiple objectives decision making problems with fuzzy goals and different importance, various kinds of fuzzy goal programming (FGP) models have been developed in the past three decades. Among them, two most widely used methods are: (1) weighted FGP, where the importance of the objectives is represented by weights (2) preemptive priority (also known as “Lexicographic”) FGP, where the priority levels of the goals are set in advance, and the trade-offs among goals placed at different priority levels are implemented strictly. This article presents a satisficing method based on FGP model, which holds that a more important objective has to be achieved as much as possible. The relaxed preemptive priority requirement in the proposed model provides a more efficient, flexible and practicable decision support compared to the weighted and the lexicographic models. In addition, the trade-off between optimization and importance requirement can be realized by the regulation parameter in the presented method. The performance of this method is evaluated by comparing its result with those of the six existing models in the literature. Copyright Springer Science+Business Media B.V. 2013

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  • Hung-Wen Cheng, 2013. "A satisficing method for fuzzy goal programming problems with different importance and priorities," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(1), pages 485-498, January.
    • Handle: RePEc:spr:qualqt:v:47:y:2013:i:1:p:485-498
    DOI: 10.1007/s11135-011-9531-0
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    References listed on IDEAS

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    1. R. E. Bellman & L. A. Zadeh, 1970. "Decision-Making in a Fuzzy Environment," Management Science, INFORMS, vol. 17(4), pages 141-164, December.
    2. Li, Shaoyuan & Hu, Chaofang, 2009. "Satisfying optimization method based on goal programming for fuzzy multiple objective optimization problem," European Journal of Operational Research, Elsevier, vol. 197(2), pages 675-684, September.
    3. Akoz, Onur & Petrovic, Dobrila, 2007. "A fuzzy goal programming method with imprecise goal hierarchy," European Journal of Operational Research, Elsevier, vol. 181(3), pages 1427-1433, September.
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    1. Min Zhou & Shasha Lu & Shukui Tan & Danping Yan & Guoliang Ou & Dianfeng Liu & Xiang Luo & Yanan Li & Lu Zhang & Zuo Zhang & Xiangbo Zhu, 2017. "A stochastic equilibrium chance-constrained programming model for municipal solid waste management of the City of Dalian, China," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(1), pages 199-218, January.
    2. Edgar Ojeda Camargo & John E. Candelo-Becerra & Alcides Santander Mercado, 2019. "Lexicographic Multi-objective Optimisation of Hybrid Power Generation Systems for Communities in Non-Interconnected Zones," International Journal of Energy Economics and Policy, Econjournals, vol. 9(3), pages 205-217.
    3. Nurullah Umarusman, 2018. "Fuzzy Goal Programming Problem Based on Minmax Approach for Optimal System Design," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 6(1), pages 177-192, June.

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