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Decision-making is a tedious and complex process. In the present competitive scenario, any incorrect decision may excessively harm an organization. Therefore, the parameters involved in the decision-making process should be looked into carefully as they may not always be of a deterministic nature. In the present study, a multiobjective nonlinear transportation problem is formulated, wherein the parameters involved in the objective functions are assumed to be fuzzy and both supply and demand are stochastic. Supply and demand are assumed to follow the exponential distribution. After converting the problem into an equivalent deterministic form, the multiobjective problem is solved using a neutrosophic compromise programming approach. A comparative study indicates that the proposed approach provides the best compromise solution, which is significantly better than the one obtained using the fuzzy programming approach. [ABSTRACT FROM AUTHOR]

Decision-making is a tedious and complex process. In the present competitive scenario, any incorrect decision may excessively harm an organization. Therefore, the parameters involved in the decision-making process should be looked into carefully as they may not always be of a deterministic nature. In the present study, a multiobjective nonlinear transportation problem is formulated, wherein the parameters involved in the objective functions are assumed to be fuzzy and both supply and demand are stochastic. Supply and demand are assumed to follow the exponential distribution. After converting the problem into an equivalent deterministic form, the multiobjective problem is solved using a neutrosophic compromise programming approach. A comparative study indicates that the proposed approach provides the best compromise solution, which is significantly better than the one obtained using the fuzzy programming approach. [ABSTRACT FROM AUTHOR]

Supplier selection plays a vital role in evolving an effective supply chain and the overall performance of organisations. Choosing suppliers may involve different levels arranged in a hierarchical structure. Decisions are made successively starting from the first level to the last level. Decision variables are partitioned between different levels and are called controlling factors. In the paper, we propose a multilevel supplier selection problem with uncertain or fuzzy demand and supply. Since objectives may be conflicting in nature, possible relaxations in the form of tolerances are provided by the upper level decision makers to avoid decision deadlocks. We use (linear) membership functions to fuzzily describe objective functions, as well as the controlling factors, and generate satisfactory solutions. We extend and present an approach to solving multilevel decision making problems when fuzzy constraints are employed. Different scenarios are constructed within a numerical illustration, based on the selection of controlling factors by the upper level decision makers. [ABSTRACT FROM AUTHOR]