Container Swap Trailer Transportation Routing Problem Based On Genetic Algorithm

In swap trailer transportation routing problems,trucks and trailers conduct swap operations at special positions called trailer points.The parallelization of stevedoring and transportation can be achieved by means of these trailer points.This logistics organization mode can be more effective than the others.Therefore,it is of great significance for studying the swap trailer transportation routing problems.In this thesis,we studied the swap trailer transportation routing problems with time windows and with customer priority,separately.In the first problem,an integer programming model with capacity and time-window constraints was established.A repairing strategy is embedded in the genetic algorithm(GA)to solve the model.The repairing strategy is executed after the crossover and mutation operation to eliminate the illegal routes.Furthermore,a parameter self-adaptive adjustment policy is designed to improve the convergence.Then numerical experiments are implemented based on the generated datasets,the performance and robust of the algorithm parameter selfadaptive adjustment policy are discussed.Finally,the results show that the improved algorithm performs better than elementary GA.In the second problem,the definition and calculation method of customer priority were given,and the corresponding mathematical model and the genetic algorithm were designed.Based on the adjusted datasets,numerical experiments were carried out to verify the effectiveness and generality of the algorithm.The research results in this thesis can effectively solve swap trailer transportation routing problems with time windows and with customer priority,which is of significance for solving the swap trailer transportation routing problems.