The modeling and solving logistic problems under uncertainty by using fuzzy logics

Logistic costs, constitute one of the most important expense items of corporations which seek methods of keeping these costs as low as possible. By doing this, corporations target to lower the costs and to increase the revenues without compromising the quality of their offerings regardless of whether they are providing goods or services. Corporations face a significant number of challenges while trying to match these targets. These problems can be solved with the assumption that all the parameters of any such problem are given as certain, however in real life, uncertainty prevails the domain of problem solution. In recent years, fuzzy logic is increasingly applied with success for modelling of the problems under uncertainty. In this work; transportation problems, single source factory localization problems, gravity localization problems, network optimization problems, assignment and transportation problems are solved with the aid of LINGO package program by modeling with a variety of fuzzy linear programming methods using principles of fuzzy logic.