Research On Dynamic Vehicle Routing Optimization Based On Two-stage Heuristic Algorithm

With the rapid growth of the national and social economy,the logistics industry has developed rapidly.Research on logistics vehicle routing planning can improve the development quality of the logistics industry.Nowadys,technologies such as the IOT,cloud computing,and Beidou navigation are widely popularized in production and life,which makes it possible to consider more real-time information when optimizing vehicle routing,and many new formats in the logistics industry also need to consider real-time information when optimizing vehicle routing.Researching the dynamic vehicle routing problem considering multiple dynamic elements is of great significance for reducing logistics costs,improving customer satisfaction,and improving the stability of the entire logistics system.On the basis of the traditional static vehicle routing problem,the dynamic vehicle routing problem is studied,and the impact of multiple dynamic elements on the optimization of vehicle routing is considered,including new customer needs,changes in customer original needs,accidental vehicle breakdowns,and traffic congestion.In addition,the heuristic algorithm for solving the vehicle routing problem is researched,and a two-stage heuristic algorithm is designed.Firstly,the development history of the dynamic vehicle routing problem and the current research status of the dynamic vehicle routing problem at home and abroad are analyzed.It is found that most of the current studies only consider one dynamic element,and the research goal is established for this problem.Through research,a solution strategy for several dynamic elements has been established,the solution strategy for dynamic information such as new demand,vehicle breakdown,etc.is to divide the dynamic problem into multiple static sub-problems by dividing time slices,and traffic congestion is regarded as different vehicle speeds in different periods,and the overall optimization strategy is adopted when the vehicle path changes.Secondly,time elements are introduced to construct a dynamic vehicle routing optimization model.The optimization goal is to reduce the total cost including vehicle departure cost,travel cost and penalty cost for violating the customer’s time window.Based on the model construction,a two-stage heuristic algorithm suitable for solving dynamic vehicle routing problem is designed.The first stage of this algorithm uses genetic algorithm to find a global better solution,and the second stage uses variable neighborhood search algorithm to search this solution deeply,thereby improving the overall optimization ability of the algorithm,and using benchmark test examples to verify the goodness of the algorithm performance.Finally,a simulation experiment was designed to solve the calculation examples with strategies and algorithms,and the optimal driving path of the vehicle under the influence of various dynamic information was obtained.The solution results obtained by using different optimization strategies and considering different dynamic elements were compared.Research conclusions are reached,it shows the feasibility of the research content in this paper and the superiority of dynamic optimization strategy,which can effectively improve the efficiency of vehicle use,reduce vehicle driving distance,and improve customer satisfaction.It provides a certain theoretical basis for the path selection of logistics vehicles under the influence of multiple dynamic elements.