Research On Vehicle Scheduling Problem Based On Genetic Simulated Annealing Algorithm

Economic globalization is booming in the 21st century. With the thorough development in market economy, logistics as the third source of profit plays an important role in every field of manufacture, distribution, transportation and consumption in our country.Distribution is a crucial tache in logistics, which is directly connected with consumers. Thus, the status of distribution is very prominent. How to realize the fast and exact distribution became an important subject that must be solved in the management of corporations. Generally, distribution means the distribution centers organize the distribution according to the frequent and small orders of different customers. The main is to assign the vehicles and plan the courses according to the assured cargo quantities, and that is the wide-researching Vehicle Scheduling Problem. Since the conditions of carriage of goods by vehicles in distribution are complex, especially the urban distribution, it is necessary to establish the more scientific and better distribution-scheduling model in order to satisfy the customers' high-quality requests.In this thesis, it has firstly given a brief summary on Vehicle Scheduling Problem. By simplifying the problem, it gives the corresponding mathematical model and the introduction of regular way of solving the problem. In the third chapter, it introduced the basic idea of Genetic Algorithm, the application of Genetic Algorithm in Vehicle Scheduling Problem. Since the Genetic Algorithm has its immanent limitations and the Simulated Annealing Algorithm has the advantages in some aspects, combined these two algorithms together just achieve the perfection. This concludes the Genetic Simulated Annealing Algorithm. In this chapter, it puts forward a kind of structure of Genetic Simulated Annealing Algorithm. Then, it introduces the steps of this algorithm. In the forth chapter, it gives a new chromosome code aiming at the simplified Vehicle Scheduling Problem model in logistics. With this coding mode, when applying Genetic Simulated Annealing Algorithm to search the lowest transport costs, this algorithm can...