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Fuzzy multi-objective solid transportation problem: genetic algorithm-based solution approach

Author

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  • Shubha Agnihotri
  • Jayesh M. Dhodiya

Abstract

This article addresses the structure of the fuzzy multi-objective solid transportation problem (FMOSTP) under the aegis of a hybrid genetic algorithm. Here, solid transportation problems (STP) are three-dimensional transportation problems in the sense that the mode of transportation is taken into account along with demand and supply constraints. Furthermore, the data structure considered in this article is assumed to be fuzzy because of the argument that the crisp data, in principle, is nearly hypothetical, and for this reason, the theory of fuzzy numbers is employed to account for the inherent impreciseness/uncertainty of the underlying system. Against this backdrop, the authors propose a matrix-based stochastic algorithm that efficiently generates an initial population. In this connection, two STPs are also posed for illustration purposes and solved using a hybrid genetic algorithm. In addition, the obtained results are compared with the fuzzy programming technique (FPT).

Suggested Citation

  • Shubha Agnihotri & Jayesh M. Dhodiya, 2024. "Fuzzy multi-objective solid transportation problem: genetic algorithm-based solution approach," International Journal of Mathematics in Operational Research, Inderscience Enterprises Ltd, vol. 29(2), pages 271-290.
    • Handle: RePEc:ids:ijmore:v:29:y:2024:i:2:p:271-290
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