Logistics Network Design and Optimization Based on Fuzzy Adaptive Differential Evolution Algorithm

The aim of this paper is to study a mixed integer nonlinear programming model.The model designs integrated distribution network to account for the optimizing the forward and reverse network simultaneously. Differential evolution is applied to solve the problem. The differential algorithm originally is for global optimization over continuous spaces. In order to adjust parameters effectively and deal with discrete variables, a fuzzy adaptive differential algorithm is developed. The fuzzy differential evolution algorithm uses fuzzy logic controllers to incorporate the value of function and individuals of the successive generations. The parameter for the mutation operation and the crossover operation are changed adaptively according to the input data. The proposed algorithm optimizes the forward and reverse logistics simultaneously and the result shows the algorithm has a rapid convergence rate.