The Research On VRP Based On Improved Genetic Algorithm

Logistics industry has developed quickly in recent years. With the logistics market becoming stronger;the competition has become more and more drastic. Distribution's effect in the whole logistics system is more important with the development of logistics industry to globalization, digitalization and integration. The high quality of logistics service required by customers and competition in the logistics service make logistics companies pay more and more attention to scientific and efficient logistics distribution management.Distribution is an important link in logistics, which is joined to consumers directly. Transportation system is the most important subsystem in distribution system, and the cost of transportation occupies 50% of that in whole logistics. So, reducing the cost of logistics begins with reducing that of transportation of logistics distribution. In the problem, whether the transportation route is rational will affect the speed, cost and benefit of distribution. Selecting rational vehicles' route can help to achieve quicker response speed to customers, improve the quality of service, increase customers' satisfaction to logistics system and reduce operational cost of service merchants. This paper has studied the core problem of the distribution —VRP by using genetic algorithm(GA).Genetic algorithm is an artificial intelligence technology of self-organization and adaptation, which imitates natural organisms' evolutionary process and mechanism to solve problems. It produces new colony and makes it achieve or approach optimization result by using colony search technique, choosing, crossover and mutation. Because of the algorithm's simple elements, achieving easily and obvious application effect, it is widely applied in combination optimization, mode identification, machinery learning, artificial being, management decision-making and so on. Genetic algorithm applies a frame of a kind of currency algorithm, and this frame is foreign to the varieties of problems.This paper puts forward an improved genetic algorithm on the base of analysingthe research on VRP in China and abroad. The improved genetic algorithm uses integer coding, penalty function to solve constraints, improves crossover operators and mutation operators and uses some operations to deal with illegal individuals until they are legal. At last we realizes the improved genetic algorithm by MATLAB. The algorithm given in this paper can obtain an optimized solution effectively and has been proved to be a good scheme to solve VRP. So, it has a high value to logistic enterprises to decrease the cost, to improve the level of logistics management, to response customers more quickly and to improve the rivalship power of the enterprise.