Model Research of Vehicle Intelligent Scheduling Problem in Distribution Center Based on Improved Differential Evolution Algorithm

With the continuous expansion of the city scale and the increasing population, people have put forward higher requirements for the speed, reliability and economy of logistics distribution. Although there have been many achievements in the research on the vehicle optimal scheduling decision model and its solution algorithm, there are some problems such as low solution efficiency, long time consumption, and easy to fall into the local optimal solution. The purpose of this paper is to study the model of vehicle scheduling problem in distribution center based on improved differential evolution algorithm. This paper firstly makes a simple analysis of the vehicle distribution route optimization problem, and points out the main factors that constitute the route optimization problem; then analyzes the principle of the differential evolution algorithm, and on this basis, the differential evolution algorithm is improved. In the experimental part, this paper takes a distribution center as the research object, and proposes the implementation steps of the algorithm of the vehicle scheduling problem based on the improved differential evolution algorithm. And test the running cost of the improved differential evolution algorithm and differential evolution algorithm. Experimental results show that applying the improved differential evolution algorithm to vehicle scheduling problems has certain practicality. When the number of iterations reaches 60, the running cost of the improved differential evolution algorithm is 1,200 yuan, and the running cost of the differential evolution algorithm is 1,300 yuan.