An Optimization Approach On Finished Vehicle Routing Problem For Low Carbon With Soft Time Windows Constraints

With the rapid development of China's economy and the improvement of people's living standards,automobile sales have risen sharply,which puts higher demands on the service of the vehicle logistics industry.At present,China's automobile logistics enterprises have a large number,service capacity is also uneven,and the distribution method is simple and takes a long time,resulting in high distribution costs of vehicle logistics enterprises,which seriously hinders the development of the vehicle logistics industry.In order to meet the needs of customers and the development trend of green logistics in our country,this paper puts forward the optimization of environmental multi-vehicle routing problem with soft time windows.First,the mathematical model of multi-objective optimization is set up with the aim of reducing transportation cost,decreasing carbon dioxide emissions and improving customer satisfaction.Then,we have designed the genetic algorithm to solve it.For improving the efficiency of finding the optimal solution,we have improved the selection and crossover operators.In the research of how to select the kinds of cars,we puts forward the application of Dijkstra algorithm to vehicle selection problem,which not only improves the efficiency of the genetic algorithm,but also enhances the search ability of the global optimal solution.Finally,the results show that the algorithm has a good performance,but when the number of customers increased exponentially,the solving speed will be decelerated.Then,we have improved the initial population according to the characteristics of the optimal solution.At the last,examples showed that the algorithm after improving can still maintain good performance.