Exploring Travelling Salesman Problem using Genetic Algorithm

Genetic Algorithms (GAs) is an evolutionary search algorithm used to find out optimal solutions for various NP problems. An effective chromosome representation, a carefully designed crossover and mutation operators are needed in GAs to achieve an efficient search. Travelling salesman problem (TSP) is a combinatorial optimization problem. It is NP complete problem and is the most commonly studied problem in the area of optimization. But the complexity of the problem goes on increasing, as the number of cities increases. The objective of this study is to solve TSP using GAs approach. In the genetic algorithm system begins from a matrix of the calculated distance between the cities to be visited by the travelling salesman and randomly chosen city sequence as the initial population. Then new generations are formed repetitively until the suitable path is reached. Genetic algorithms use techniques inspired by evolutionary biology such as inheritance, mutation, selection, and crossover. Keywords--Genetic Algorithm, TSP, Selection, Crossover, Mutation, Enhanced Edge Recombination.