Genetic Algorithm Approach to Search the Shortest Path for Traveling in Ayeyarwaddy Division

Abstract

Genetic Algorithms (GAs) are adaptive heuristic search algorithms which are premised on the evolutionary ideas of natural selection and gene types. Basically, several random sets of parameters are applied to an algorithm and a fitness value (optimization value) is calculated for each. Based on this fitness values, the best sets are mixed (this is a combination of Selection, Crossover and Mutation) together and new sets are again applied to the algorithm until an optimal parameter(s) are obtained. This paper presents a genetic algorithm approach to search the shortest path for traveling in Ayeyarwaddy Division. This is based on the analogy of finding the shortest possible distance between towns or cities in a graph or a map. Typically this is represented by a graph with each node representing a city and each edge being a path between two cities. The algorithm has been tested for a road map containing about 127 cities and the experimental results guarantee to provide acceptably good solutions for the given search space.