Parameters Sensitive Analyses for Using Genetic Algorithm to Solve Continuous Network Design Problems

Abstract

In this paper, the authors will discuss the parameters' settings using genetic algorithm to solve continuous network design problems (CNDP). The CNDP is formulated as a bi-level programming model. A sensitive analysis method, one-at-a-time design, is used to analyze the effects of the parameters. The analysis demonstrated that the setting of population size has clear effects on the solution; the effects of crossover probability and mutation probability are less than the effects of their combinations. The fields of these parameters are also given in this paper, which avoid to set them blindly in algorithm designs.