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A multilevel decision making model for the supplier selection problem in a fuzzy situation

Author

Listed:
  • Ahmad Yusuf Adhami
  • Syed Mohd Muneeb
  • Mohammad Asim Nomani

Abstract

Supplier selection plays a vital role in evolving an effective supply chain and the overall performance of organisations. Choosing suppliers may involve different levels arranged in a hierarchical structure. Decisions are made successively starting from the first level to the last level. Decision variables are partitioned between different levels and are called controlling factors. In the paper, we propose a multilevel supplier selection problem with uncertain or fuzzy demand and supply. Since objectives may be conflicting in nature, possible relaxations in the form of tolerances are provided by the upper level decision makers to avoid decision deadlocks. We use (linear) membership functions to fuzzily describe objective functions, as well as the controlling factors, and generate satisfactory solutions. We extend and present an approach to solving multilevel decision making problems when fuzzy constraints are employed. Different scenarios are constructed within a numerical illustration, based on the selection of controlling factors by the upper level decision makers.

Suggested Citation

  • Ahmad Yusuf Adhami & Syed Mohd Muneeb & Mohammad Asim Nomani, 2017. "A multilevel decision making model for the supplier selection problem in a fuzzy situation," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 27(4), pages 5-26.
    • Handle: RePEc:wut:journl:v:4:y:2017:p:5-26:id:1314
    DOI: 10.5277/ord170401
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    References listed on IDEAS

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    1. Sinha, Surabhi & Sinha, S. B., 2002. "KKT transformation approach for multi-objective multi-level linear programming problems," European Journal of Operational Research, Elsevier, vol. 143(1), pages 19-31, November.
    2. Li, Lei & Zabinsky, Zelda B., 2011. "Incorporating uncertainty into a supplier selection problem," International Journal of Production Economics, Elsevier, vol. 134(2), pages 344-356, December.
    3. Chen, Chen-Tung & Lin, Ching-Torng & Huang, Sue-Fn, 2006. "A fuzzy approach for supplier evaluation and selection in supply chain management," International Journal of Production Economics, Elsevier, vol. 102(2), pages 289-301, August.
    4. Kumar, Manoj & Vrat, Prem & Shankar, Ravi, 2006. "A fuzzy programming approach for vendor selection problem in a supply chain," International Journal of Production Economics, Elsevier, vol. 101(2), pages 273-285, June.
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    Cited by:

    1. Syed Mohd Muneeb & Ahmad Yusuf Adhami & Zainab Asim & Syed Aqib Jalil, 2019. "Bi-level decision making models for advertising allocation problem under fuzzy environment," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(2), pages 160-172, April.
    2. Vandana Goyal & Namrata Rani & Deepak Gupta, 2022. "An algorithm for quadratically constrained multi-objective quadratic fractional programming with pentagonal fuzzy numbers," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 32(1), pages 49-71.
    3. Muneeb, Syed Mohd & Asim, Zainab & Hajiaghaei-Keshteli, Mostafa & Abbas, Haidar, 2023. "A multi-objective integrated supplier selection-production-distribution model for re-furbished products: Towards a circular economy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 175(C).
    4. Srikant Gupta & Irfan Ali & Aquil Ahmed, 2018. "Multi-objective bi-level supply chain network order allocation problem under fuzziness," OPSEARCH, Springer;Operational Research Society of India, vol. 55(3), pages 721-748, November.
    5. Syed Aqib Jalil & Shakeel Javaid & Syed Mohd Muneeb, 2018. "A decentralized multi-level decision making model for solid transportation problem with uncertainty," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 9(5), pages 1022-1033, October.

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