IDEAS home Printed from https://ideas.repec.org/a/spr/qualqt/v47y2013i1p485-498.html
   My bibliography  Save this article

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

Author

Listed:
  • 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

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11135-011-9531-0
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11135-011-9531-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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. 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.
    3. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Firoz Ahmad, 2022. "Interactive neutrosophic optimization technique for multiobjective programming problems: an application to pharmaceutical supply chain management," Annals of Operations Research, Springer, vol. 311(2), pages 551-585, April.
    2. Lotfi, M.M. & Torabi, S.A., 2011. "A fuzzy goal programming approach for mid-term assortment planning in supermarkets," European Journal of Operational Research, Elsevier, vol. 213(2), pages 430-441, September.
    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.
    4. 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.
    5. Vuciterna, Rina & Thomsen, Michael & Popp, Jennie & Musliu, Arben, 2017. "Efficiency and Competitiveness of Kosovo Raspberry Producers," 2017 Annual Meeting, February 4-7, 2017, Mobile, Alabama 252770, Southern Agricultural Economics Association.
    6. Scott, James & Ho, William & Dey, Prasanta K. & Talluri, Srinivas, 2015. "A decision support system for supplier selection and order allocation in stochastic, multi-stakeholder and multi-criteria environments," International Journal of Production Economics, Elsevier, vol. 166(C), pages 226-237.
    7. Berna Tektas Sivrikaya & Ferhan Cebi & Hasan Hüseyin Turan & Nihat Kasap & Dursun Delen, 2017. "A fuzzy long-term investment planning model for a GenCo in a hybrid electricity market considering climate change impacts," Information Systems Frontiers, Springer, vol. 19(5), pages 975-991, October.
    8. Collan, Mikael, 2008. "New Method for Real Option Valuation Using Fuzzy Numbers," Working Papers 466, IAMSR, Åbo Akademi.
    9. Kim, Jong Soon & Whang, Kyu-Seung, 1998. "A tolerance approach to the fuzzy goal programming problems with unbalanced triangular membership function," European Journal of Operational Research, Elsevier, vol. 107(3), pages 614-624, June.
    10. Berna Tektaş & Hasan Hüseyin Turan & Nihat Kasap & Ferhan Çebi & Dursun Delen, 2022. "A Fuzzy Prescriptive Analytics Approach to Power Generation Capacity Planning," Energies, MDPI, vol. 15(9), pages 1-26, April.
    11. Chen, Lisa Y. & Wang, Tien-Chin, 2009. "Optimizing partners' choice in IS/IT outsourcing projects: The strategic decision of fuzzy VIKOR," International Journal of Production Economics, Elsevier, vol. 120(1), pages 233-242, July.
    12. Víctor G. Alfaro-García & Anna M. Gil-Lafuente & Gerardo G. Alfaro Calderón, 2017. "A fuzzy approach to a municipality grouping model towards creation of synergies," Computational and Mathematical Organization Theory, Springer, vol. 23(3), pages 391-408, September.
    13. Aghayi, Nazila & Maleki, Bentolhoda, 2016. "Efficiency measurement of DMUs with undesirable outputs under uncertainty based on the directional distance function: Application on bank industry," Energy, Elsevier, vol. 112(C), pages 376-387.
    14. Wenyao Niu & Yuan Rong & Liying Yu & Lu Huang, 2022. "A Novel Hybrid Group Decision Making Approach Based on EDAS and Regret Theory under a Fermatean Cubic Fuzzy Environment," Mathematics, MDPI, vol. 10(17), pages 1-30, August.
    15. de Andres-Sanchez, Jorge, 2007. "Claim reserving with fuzzy regression and Taylor's geometric separation method," Insurance: Mathematics and Economics, Elsevier, vol. 40(1), pages 145-163, January.
    16. Mikhailov, L., 2004. "A fuzzy approach to deriving priorities from interval pairwise comparison judgements," European Journal of Operational Research, Elsevier, vol. 159(3), pages 687-704, December.
    17. Hongyi Sun & Bingqian Zhang & Wenbin Ni, 2022. "A Hybrid Model Based on SEM and Fuzzy TOPSIS for Supplier Selection," Mathematics, MDPI, vol. 10(19), pages 1-19, September.
    18. Liu, Yong-Jun & Zhang, Wei-Guo, 2015. "A multi-period fuzzy portfolio optimization model with minimum transaction lots," European Journal of Operational Research, Elsevier, vol. 242(3), pages 933-941.
    19. Sakawa, Masatoshi & Kato, Kosuke, 1998. "An interactive fuzzy satisficing method for structured multiobjective linear fractional programs with fuzzy numbers," European Journal of Operational Research, Elsevier, vol. 107(3), pages 575-589, June.
    20. Sajid Ali & Sang-Moon Lee & Choon-Man Jang, 2017. "Determination of the Most Optimal On-Shore Wind Farm Site Location Using a GIS-MCDM Methodology: Evaluating the Case of South Korea," Energies, MDPI, vol. 10(12), pages 1-22, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:qualqt:v:47:y:2013:i:1:p:485-498. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.