Abstract
This paper focuses on modeling and optimization of entropy-based uncertain multi-item solid transportation problems (MISTPs), in which direct costs, supplies, demands, conveyance capacities are uncertain nature. The purpose is to minimize the total uncertain cost via maximum entropy which ensures uniform delivery of products from sources to destinations through conveyances. The expected value programming and expected constrained programming models for optimizing the entropy-based uncertain MISTPs are constructed. These models are based on uncertainty theory. Subsequently, the constructed models are converted into their deterministic equivalences which are solved using two known mathematical programming methods. Finally, a numerical example is given to illustrate the models.
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