A Dual Hesitant Fuzzy Optimization Approach for Solving the Multi-Objective Multi-Item Just-in-Time Transportation Problem

This paper presents a study on the multi-objective multi-item Just-in-Time transportation problem (MJTP) under a dual hesitant fuzzy environment. In real-world transportation systems, uncertainty and ambiguity often arise in cost, profit, and delivery parameters; therefore, dual hesitant fuzzy numbers are employed to represent such imprecise information effectively. The Just-in-Time concept is incorporated to ensure that goods are delivered to destinations within the scheduled time, thereby reducing inventory holding costs and improving system efficiency. A mathematical model of the MJTP is formulated considering multiple conflicting objectives, including minimization of transportation cost, maximization of profit, and adherence to delivery schedules. To obtain a compromise solution, a goal programming approach is utilized to transform the multi-objective problem into a solvable form under the fuzzy environment. A numerical example is provided to demonstrate the applicability and effectiveness of the proposed model and solution procedure. The results confirm that the developed approach can handle uncertainty efficiently while satisfying time-dependent delivery requirements. Finally, conclusions and potential directions for future research are discussed.