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Solving the Multiobjective Fractional Transportation Problem through the Neutrosophic Goal Programming Approach

Author

Listed:
  • C. Veeramani
  • S. A. Edalatpanah
  • S. Sharanya
  • Dragan PamuÄ ar

Abstract

Nowadays, the transportation problem is a multiobjective decision-making problem. It involves deciding to determine the ideal transportation setup that matches the decision maker’s preferences while taking into account competing objectives/criteria such as transportation cost, transportation time, and environmental and social concerns. This study presents a general framework of the multiobjective fractional transportation problem (MOFTP) to deal with such complex scenarios. This paper’s major goal is to propose a solution methodology to solve the MOFTP based on a neutrosophic goal programming (NGP) approach. By obtaining the optimal compromise solution using three memberships, namely, truth membership, indeterminacy membership, and falsity membership, the suggested technique gives a novel insight into solving the MOFTP. A real-world problem such as selling wind turbine blades’ problem and a numerical example are used to demonstrate the efficacy and superiority of the proposed method.

Suggested Citation

  • C. Veeramani & S. A. Edalatpanah & S. Sharanya & Dragan PamuÄ ar, 2021. "Solving the Multiobjective Fractional Transportation Problem through the Neutrosophic Goal Programming Approach," Discrete Dynamics in Nature and Society, Hindawi, vol. 2021, pages 1-17, August.
  • Handle: RePEc:hin:jnddns:7308042
    DOI: 10.1155/2021/7308042
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    Cited by:

    1. 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.
    2. Feng Guo & Liguo Jiao, 2023. "A new scheme for approximating the weakly efficient solution set of vector rational optimization problems," Journal of Global Optimization, Springer, vol. 86(4), pages 905-930, August.

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