Using One-at-a-Time Sensitivity Analysis Designs for Genetic Algorithm Solving Continuous Network Design Problems

This paper is focus on the parameters settings using genetic algorithm to solve continuous network design problems (CNDP). The CNDP is formulated as a bi-level programming model. The sensitive analyses method, one-at-a-time designs, is used to analyze the effects of parameters. The analyses demonstrated that the setting of population size has clear effects to 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.