Based On Genetic Algorithm Car Logistics Problem

The genetic algorithm, proposed by Professor J. Holland, is a class of stochastic optimization search algorithm for biological mechanisms in natural selection and natural genetic. The genetic algorithm is a powerful random searching optimization techniques and widely used in machine learning, combinatorial optimization, planning and design, adaptive control and artificial life and other fields, especially in dealing with the complex and difficult nonlinear problems. So, we can say that the genetic algorithm is one of the key intelligent computing techniques in the 21st century.The logistics, usually known as the third profit source, is an important industry in social development. Logistics distribution is one of the key areas connected with the consumer directly and is usually understood as the process for the goods sent to the consignee. Transport presents a very important position in the logistics industry, and have a great impact on the logistics cost, then rational planning of transport vehicles plays a vital role to reduce the cost. The main contents of this paper is to use genetic algorithms to solve the problem of vehicle routing. This paper firstly analyzes the current problem of vehicle routing research status at home and abroad, and gives the vehicle routing problem with time windows (VRPTW), then introduces the theory of genetic algorithm to VRPTW and takes an example for the problem formulation, modeling, algorithm design and implement for this algorithm. Finally, based on the traditional genetic algorithm, we present an improved genetic algorithm and compare the genetic algorithm with the traditional method, reflecting the improved genetic algorithm for the feasibility and superiority.