A Multi-Objective Stochastic Solid Transportation Problem with the Supply, Demand, and Conveyance Capacity Following the Weibull Distribution

Amrit Das and Gyu M. Lee
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Amrit Das: Department of Mathematics, VIT University, Vellore 632014, India
Gyu M. Lee: Department of Industrial Engineering, Pusan National University, Busan 46241, Korea

Mathematics, 2021, vol. 9, issue 15, 1-21

Abstract: This study addresses a multi-objective stochastic solid transportation problem (MOSSTP) with uncertainties in supply, demand, and conveyance capacity, following the Weibull distribution. This study aims to minimize multiple transportation costs in a solid transportation problem (STP) under probabilistic inequality constraints. The MOSSTP is expressed as a chance-constrained programming problem, and the probabilistic constraints are incorporated to ensure that the supply, demand, and conveyance capacity are satisfied with specified probabilities. The global criterion method and fuzzy goal programming approach have been used to solve multi-objective optimization problems. Computational results demonstrate the effectiveness of the proposed models and methodology for the MOSSTP under uncertainty. A sensitivity analysis is conducted to understand the sensitivity of parameters in the proposed model.

Keywords: multi-objective stochastic solid transportation problem; Weibull distribution; chance-constrained programming; global criterion method; fuzzy goal programming (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
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