Research On Vehicle Routing Problem Based On Immune Genetic Algorithm

With the development of economic globalization, the modern logistics has become the hot spot which some people in the world pay attention to. The enterprises gradually change the foresight to logistics, which was called"the third profit source",but how to match the allocation vehicles route through the reasonable plan, to reduce the transportation cost, becomes the problem which the enterprise policy-makers and the theory researchers pay attention to.The vehicle routing problem is the typical combined optimization problem, which belongs to a kind of NP difficult problem, and has high computation complexity. After doing some research on vehicle routing problem, this research establishes the model of vehicle routing problem, and presents a detailed mathematical description. Then it introduces the fundamental theory and applications of genetic algorithm and the immunity algorithm, and summarizes respective good and bad points. The antibody in Immune algorithm is evaluated and selected through the calculation of the affinity between antibody and antigen or the one between antibodies. The search efficiency near the optimum point is enhanced through the promotion and restrain of antibodies. The possibility of stagnation into local optimum in the iteration process is decreased through the memory cell, thus the integer search ability is enhanced. The immune genetic algorithm unifies the immune algorithm and the genetic algorithm. It can overcome precocious restraining, speed up the search speed, and enhance the algorithm search ability overall.Finally, this research gives the detailed flow of the immune genetic algorithm in solving the VRP problem.It realizes this algorithm using the Java language programming. The empirical datum has confirmed this algorithm's feasibility. By contrasting the feasibility of this algorithm to the basic genetic algorithm, it demonstrates this algorithm's superiority in resolving the VRP problem.