A Novel Fuzzy Approach for Solving A Fully Fuzzy Multi-Objective Transportation Problem Using Triangular Fuzzy Numbers - Sharma, Priyanka; Kumar, Narendra; Yadav, Krishan Kumar (International Journal of Industrial Engineering: Theory, Applications and Practice, 2026)
The transportation problem (TP) is a classical optimization model in operations research and logistics and represents a special class of linear programming problems. In practical decision-making scenarios, multiple conflicting objectives often need to be optimized simultaneously under uncertain conditions. To address this uncertainty, fuzzy concepts are used to model the imprecision in transportation costs, supplies, and demands. Although several methods have been developed for solving fully fuzzy multi-objective transportation problems (MOTP), classical solution techniques such as the North-West Corner Rule have rarely been extended to fully fuzzy environments. This paper proposes a new fuzzy extension of the North-West Corner Rule to obtain a compromise-efficient solution for a fully fuzzy multi-objective transportation problem, in which all parameters are represented by triangular fuzzy numbers. The fuzzy multi-objective problem is transformed into a fuzzy single-objective transportation problem (SOTP), and the proposed approach is used to generate an initial fuzzy basic feasible solution, which is further improved using the fuzzy generalized modified distribution (FG-MODI) method. Numerical examples demonstrate that the proposed method yields fuzzy optimal solutions comparable to existing techniques while requiring fewer computational steps, thereby highlighting its efficiency and simplicity. The method is easy to implement and suiTable for real-world transportation problems characterized by uncertainty. Additional analytical metrics, such as sensitivity and compromise analysis, further validate the robustness and effectiveness of the proposed method.