Application Of Immune Algorithm On Vehicle Scheduling Problem Of Logistics Distribution

With the development in science and technology, Logistics system has gradually been dominant for the society economics, and the logistics gross cost plays an important role in GDP. Logistics distribution is an operation linking between enterprise and consumer directly, and it holds considerable high proportion in variable cost of logistic. Vehicle Scheduling Problem (VSP) in distribution takes great effect on distribution cost and benefit of enterprise, especially in distributing for multi consumers. Using a reasonable and scientific method in Vehicle scheduling Problem is a very important action of logistics distribution. At present vehicle scheduling problem has been focus of many scholars to study.Biological Immune System (BIS) is a highly distributive and adaptive leaning system, having perfect function to resist invading of foreign pathogeny and the ability learn, remember and adjust adaptively to keep the stabilization inside the body. According to BIS holds strong ability of information handling, especially in complete parallel and distributive way to carry out complicated computation, so it has become a valuable researching subject. Artificial Immune Algorithm (AIA) is a kind of new algorithm which is base on the biological immune system, intelligentized search optimum solution has overwhelming advantages over the evolutionary algorithm, this kind of algorithm has been used in many fields, such as pattern recognition, Artificial intelligence, unconventionality and malfunction diagnosis, This method shows excellent performance and high efficiency.On the basis of researching the optimizing model on logistics vehicle scheduling, this paper introduces Clonal Selection Algorithm (CSA) into the model of the vehicle scheduling problem to establish an optimizing model on logistics vehicle scheduling problem for the coal transport and distribution system in Shanxi province. The result of experimental calculations demonstrate that the optimal or nearly optimal solutions to the logistic vehicle scheduling problem can be easily obtained by using immune algorithm. this optimizing model shows prominent capability and strong foreground in practical application.