Research On Vehicle Routing Problem With Dynamic Demands Based On Swarm Intelligence

Thanks to the convenient communication brought by the mobile Internet,customers can submit or cancel their delivery demands at any time.In the case of dynamically changing customer demands,how to plan routes to respond to customer demands in time and serve customers as many as possible,thereby increasing customer satisfaction and reducing logistics cost become an open issue.Besides,the research on the traditional vehicle routing problem pays less attention to real-world road networks in the city,which limits its applicability on practical vehicle routing problems.To solve the above problems,this dissertation analyzes the vehicle routing problem with the road network,constructs a mathematical model of this problem,and establishes a test data set based on the road network in Nanshan district,Shenzhen.In this dissertation,a hybrid algorithm based on swarm intelligence is proposed to handle the vehicle routing problem with the road network.In the proposed algorithm,the clustering operation in the brain storm optimization algorithm helps the ant colony system algorithm learn similar features in the same category to speed up the convergence.A local search algorithm is used to search more space to maintain the diversity of solutions.The efficacy of the hybrid algorithm is verified through the comparison experiment on the real-world road network.This dissertation considers the vehicle routing problem in a dynamic demand scenario based on the vehicle routing problem with the road network.To deal with the problem,this dissertation studies the dynamic processing strategy in dynamic vehicle routing problems and proposes a rolling periodic processing strategy to determine the appropriate time to transform the dynamic problem into a static problem(i.e.,the vehicle routing problem with the road network).To reduce the distribution cost and serve customers as many as possible,this dissertation further proposes a repeated insertion algorithm to solve the problem of traditional insertion algorithms failing to serve customers due to the underutilization of original path information.Finally,simulation experiments verify the efficacy of the proposed rolling cycle processing strategy and repeated insertion algorithm.