Research on location selection based on genetic and simulated annealing algorithm

Abstract

When dealing with the problem of location selection, one must optimize multiple objective functions. The combination of genetic algorithms and simulated annealing algorithm can improve the solution efficiency and solve the premature convergence problem caused by the genetic algorithm. Using the logistics distribution system as an example, we established a terminal distribution model according to the characteristics and requirements. Based on the mathematic model and the analysis on influencing factors of the transportation costs, we conducted a study on the location selection of distribution center, and subsequently designed and implemented the corresponding genetic and simulated annealing algorithm, which could reduce delivery cost and optimize distribution models. © 2012 Springer-Verlag Berlin Heidelberg.