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Application of intuitionistic fuzzy optimization technique in transportation models

Author

Listed:
  • Deepika Rani

    (Indian Institute of Technology)

  • T. R. Gulati

    (Indian Institute of Technology)

Abstract

The transportation of products from one place to another is not as simple as considered in the classical transportation model. There are various real life factors, which effect the transportation. This paper studies a solid transportation problem with heterogeneous products to be transported from supply points to demand points taking into consideration the safety factors while transporting. An additional constraint on the budget at each destination is also considered. To reflect the uncertainty in real life situations, transportation parameters are taken as fuzzy numbers. The proposed algorithm proceeds by transforming the problem to a deterministic model using the interval approximation of the fuzzy numbers and applying the intuitionistic fuzzy programming technique with different types of membership and non-membership functions. LINGO software is then used to solve the final model and get the optimal solution. The performance of the proposed approach is shown with a numerical example.

Suggested Citation

  • Deepika Rani & T. R. Gulati, 2016. "Application of intuitionistic fuzzy optimization technique in transportation models," OPSEARCH, Springer;Operational Research Society of India, vol. 53(4), pages 761-777, December.
  • Handle: RePEc:spr:opsear:v:53:y:2016:i:4:d:10.1007_s12597-016-0258-5
    DOI: 10.1007/s12597-016-0258-5
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    References listed on IDEAS

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    1. Vincent F. Yu & Kuo-Jen Hu & An-Yuan Chang, 2015. "An interactive approach for the multi-objective transportation problem with interval parameters," International Journal of Production Research, Taylor & Francis Journals, vol. 53(4), pages 1051-1064, February.
    2. Das, S. K. & Goswami, A. & Alam, S. S., 1999. "Multiobjective transportation problem with interval cost, source and destination parameters," European Journal of Operational Research, Elsevier, vol. 117(1), pages 100-112, August.
    3. Jimenez, F. & Verdegay, J. L., 1999. "Solving fuzzy solid transportation problems by an evolutionary algorithm based parametric approach," European Journal of Operational Research, Elsevier, vol. 117(3), pages 485-510, September.
    4. Dalbinder Kaur & Sathi Mukherjee & Kajla Basu, 2015. "Solution of a Multi-Objective and Multi-Index Real-Life Transportation Problem Using Different Fuzzy Membership Functions," Journal of Optimization Theory and Applications, Springer, vol. 164(2), pages 666-678, February.
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    Cited by:

    1. Prachi Agrawal & Talari Ganesh, 2020. "Fuzzy fractional stochastic transportation problem involving exponential distribution," OPSEARCH, Springer;Operational Research Society of India, vol. 57(4), pages 1093-1114, December.

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