Developing a Genetic Algorithm for Solving Shortest Path Problem

Routing is gaining prime importance in our increasingly mobile and highly Information Technology enabled world. The shortest path problem is widely applied in transportation, communication and computer networks. It addresses the challenges of determining a path with minimum distance, time or cost from a source to the destination. This paper introduces a novel Genetic Algorithm (GA) approach to solve the shortest path problem. A connected graph is assumed in which all the weights of the paths are positive. New mutations as well as crossover parameters are defined. The use of mutation parameters depends on the extent of the area under consideration, and the distance between the start and end points. In order to evaluate the proposed algorithm, an urban road map is selected. In all case studies, the algorithm was successful in determining the shortest path. The details of the experimental results are discussed and presented in the paper. Key-Words: Genetic Algorithm, Shortest path problem, Mutation, Crossover, Graph theory.