Application of Genetic Algorithm in modeling of Shortest Path problem

For a long time, people have been looking for the best way to solve problems to improve work efficiency. Shortest path as a figure with a classical problem in the study of network technology in computer science, communications, and operations research, geographic information science and other fields has a very wide range of applications, for solving the problem is not only has important theoretical significance, but also has important practical value, the problem solving algorithm design and improving the research has important significance [1-3]. This paper introduces several commonly used algorithms to solve the shortest path problem, analyses their advantages and disadvantages. Then Genetic Algorithm is introduced and the results is compared with Simulated Annealing Algorithm. The results of comparison shows that the Genetic Algorithm is much better than Simulated Annealing Algorithm in this problem. In many existing literatures, the author only elaborates a certain method or solves a specific problem through a certain method, which to a large extent makes the advantages of the method described in the literature unable to be fully displayed. In this paper, a great improvement has been made in this aspect. This Simulated Annealing Algorithm is introduced while the Genetic Algorithm is described. Simulation results show that Genetic Algorithm is more effective than Simulated Annealing Algorithm in path planning and result optimization in solving the shortest path problem.