Research On Optimization Of Vehicle Routing For Multiple Vehicle Models In Logistics Delivery

In recent years,China’s logistics and distribution industry has developed rapidly,and energy and environmental issues have also become a topic of concern for people.Many countries have formulated policies and international agreements related to carbon emissions to reduce greenhouse gas emissions.Logistics delivery is a high energy consumption process,and energy conservation and emission reduction are necessary in this industry.In addition,in typical vehicle routing problems,road conditions and customer needs are usually considered deterministic,but in actual environments,demand is stochastic and road conditions are sudden,all of which will affect delivery costs.Aiming at the problem of multi-vehicle dynamic routing optimization under low carbon conditions,the research process was divided into two stages: pre-optimization and dynamic adjustment.The optimization model was constructed with the lowest total cost as the objective function,and the improved adaptive genetic algorithm(IAGA)was used to solve the model.In the pre-optimization stage,IAGA algorithm is used to generate the initial distribution scheme under the constraints of meeting the store demand,returns,vehicle fuel volume,working hours and road conditions.In the dynamic adjustment stage,the changes in store demand,road conditions,temporary returns,as well as the current distribution vehicle location,cargo load and fuel volume are integrated.Through experimental analysis,the feasibility of the model and algorithm is verified,and the total cost is effectively reduced.The real-time control and monitoring page of logistics distribution designed and developed is easy to adjust in real time according to dynamic events.The planned distribution scheme and distribution route are displayed on the human-computer interaction page,which provides a good reference for the formulation of distribution strategies for enterprises.