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

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.

The Stochastic Transportation Problem with Imprecise Data using Lomax Distribution

“…Neutrosophic Transportation Problems (NTP) have recently been proposed as a way to use optimization techniques with unknown and indeterminate variables. Furthermore, many researchers have proposed Fuzzy Optimization Techniques (FOT), the Single-valued Trapezoidal Neutrosophic Transportation Problem (SVTNTP) [22], the Commercial Traveler Problem (CTP) [29], and a two-stage conventional transportation model to distribute relief aid to victims in uncertain scenarios [15] and multi-objective stochastic solid transportation problem (MOSSTP) uncertainity with weibull distribution [12]. In this paper proposed the SFTPMC, the stochastic transportation problem with imprecise data using the Lomax distribution provides a valuable tool for addressing the challenges of transportation planning and logistics in an uncertain environment, and it helps decision makers make more accurate and robust decisions by considering the stochastic nature of various factors and incorporating the Lomax distribution for modeling imprecise data.…”

Navigating uncertain distribution problem: a new approach for resolution optimization of transportation with several objectives under uncertainty

“…A technique for resolving MOSSTP in the presence of uncertainty by recasting it as a chance-constrained programming problem and employing fuzzy goal programming and the global criterion method to quickly find effective solutions (Das and Lee, 2021). A weighted goal programming method that, using a numerical example, discovers compromise solutions for multi-objective transportation problems following the decision-maker's priorities (Joshi et al, 2022b).…”

“…Using a fuzzy technique, multiple-choice parameters, and random variables, a transportation problem with multiple objectives is solved (Nasseri and Bavandi, 2020). b fuzzy goal programming approach (Das and Lee, 2021).…”