Abstract:Car flow routing optimization is decomposed into two parts:the evaluative function computing of car flow order and the car flow order permutation optimization.The paper first presents the definition of the function to evaluate the order,and then the introduction of the traveling salesman problem.By inducing that the car flow order permutation optimization is traveling salesman problem,an analysis is made of the computational complexity of the car flow routing optimization.The paper also presents a genetic algorithm with designing of priority weight coding,fitness function of population individuals and relevant genetic operation.And simulation results based on a real case are given.Compared with tabu search algorithm, genetic algorithm is lower in computational precision while retaining such advantages of low computing cost and low request of hardware.Therefore,the chioce of the method is based on the real situation,and a combination of the two methods is proposed if permission.
