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Multi-objective fuzzy transportation problem with fuzzy decision variables - NSGA-II approach

Author

Listed:
  • Admasu Tadesse
  • Srikumar Acharya
  • Manoranjan Sahoo

Abstract

In this paper, we consider a multi-objective fuzzy transportation problem with a fuzzy decision variable, with main objective and constraint parameters (supply and demand) considered to be triangular fuzzy numbers. Ranking function is used to convert fuzziness of objective and constraint functions into their equivalent crisp form. The crisp multi-objective transportation problem is solved using the non-dominated sorting genetic algorithm-II (NSGA-II), which is coded in MATLAB. A case study is provided to illustrate the methodology.

Suggested Citation

  • Admasu Tadesse & Srikumar Acharya & Manoranjan Sahoo, 2023. "Multi-objective fuzzy transportation problem with fuzzy decision variables - NSGA-II approach," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 45(3), pages 398-415.
    • Handle: RePEc:ids:ijisen:v:45:y:2023:i:3:p:398-415
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