Optimization Of Vehicle Routing Under Urban Traffic Regulations

It is well-known that urban distribution has played a more and more important role in our lives. On the one hand, urban distribution accelerates the circulation of commodity、improves the development of urban economy and contributes to the convenience of our daily life. On the other hand, it brings a large number of negative problems such as air pollution, energy consumption and traffic jam. Therefore, many large and medium cities have implemented restrictive regulations. Freight vehicles are granted merely access in certain areas of the city and during specified periods of a day which make trouble for carriers. Under these circumstances, this paper proposes the optimization model of vehicle routing problem with soft time window under urban traffic regulations based on time recursive matrix. A hybrid Genetic Algorithm is given. The variation trend of optimized solutions in different restrictive conditions indicate the effectiveness and practicability of proposed model and algorithm.Firstly, this paper introduces the relationship of logistics and distribution. Then this paper analyzes the influence that traffic regulations make on city urban, including environment, economy and society. The core of city distribution is vehicle routing problem. Before the mathematic formulation is proposed, this paper introduces the ordinary vehicle routing problem. The mathematic formulation is based on soft time recursive matrix. The goals consist of number of vehicles used, total distances traveled, carbon emissions and time window violation. Traffic regulations act as constraints of restricted roads and time access in formulation. Other constraints contains capacity limits and time window of customers and so on. Aim to solve vehicle routing problem under traffic regulations, a hybrid genetic algorithm is designed. This paper gives concept, characteristic and workflow of genetic algorithm, then stresses on hybrid genetic algorithm including coding, initial population combined heuristic rule, selection, crossover and mutation operations. Finally, based Solomon benchmark data, this paper compares and analyzes routing solutions in different restricted conditions.