Research On Vehicle Routing Problem Based On Modified Genetic Algorithms

With the rapid development of modern economy, the wide spread of Internet applications, as the "third source of profit" industry,logistics and distribution is playing an increasingly large daily role. By great attention to domestic and international major companies such as Carrefour, Wal-Mart, Amazon, these outstanding international enterprise. That the reason why the market has a great monopoly and a very low price to attract more and more people at home consumption, in addition to the enterprise itself has strong capital and strong brand, but also because of its modern logistics and distribution methods.The vehicle scheduling problem (Vehicle Routing Problem, called VRP) is the most important part of logistics and distribution. Solving the vehicle scheduling problem, to some extent has been effectively solved the logistics problem, saving logistics costs, thereby improving enterprise productivity. Therefore, this research in solving practical problems has great significance, how to effectively save transport costs, reduce costs, attract more customers, is taken attention by more and more people.Because the vehicle scheduling problem is NP-hard problem, belongs to combinatorial optimization problems, the complexity of the problem is proportional to the scale of the problem.It is hard to find the exact effective solution to slove the problem currently. There are many algorithm for solving the problem present, generally can be divided into exact algorithm and heuristic algorithms. In this paper we mainly use the genetic algorithm, which is particularly suitable for solving combinatorial optimization problems in the global search algorithm to solve the vehicle scheduling problem, genetic algorithm is based on Darwin's "survival of the fittest" evolutionary,which is the principles of biological evolution theory. Through evolutionary mechanism simulation, it has good global search capability to solve many problems and has broad applicability.This paper firstly introduces the research background of the vehicle scheduling problem, significance, propose and current development status, we can know some knowledge about the vehicle scheduling issues. Secondly we focuse on describing the vehicle scheduling problem, take a brief analysis of the difference between VRP and TSP, then we establish the vehicle scheduling problem mathematical model, and give the classification and the solution of the vehicle scheduling problem. Chapter III detailed the knowledge of the genetic algorithm, including the development of genetic algorithms produce, working principle, the basic concept operation features, applications, research trends and the future of the development, through these,we can have a comprehensive understanding of the genetic algorithm. In the next chapter we use the genetic algorithm to design the vehicle scheduling problem, in chapter V we give an improved genetic algorithm for vehicle scheduling problem on a specific experimental study, then we analyze the experimental results. Finally, we take a brief description and the prospect of the improved genetic algorithm to solve the vehicle scheduling problem,at last we point the future research direction.