A STUDY OF TRAVELLING SALESMAN PROBLEM USING REINFORCEMENT LEARNING OVER GENETIC ALGORITHM

Abstract

This paper represents the applications of Genetic Algorithm (GA) to solve a Travelling Salesman
problem (TSP). TSP is a simple to describe and mathematically well characterized problem but it is quite difficult to solve. This is a NP-hard type problem i.e. this problem is hard as the hardest problem in NPcomplete space. We present the Crossover and Mutation operators, sorting of the solutions to calculate the bestoptimal solutions. Previously, a numerical illustration was used to signify the model with the techniques. This paper employs Reinforcement Learning to solve the Traveling Salesman problem in the mean of Genetic Algorithm. The technique proposes a model (actions, states, reinforcements).