Moving Target Travelling Salesman Problem using Genetic Algorithm

Abstract

ABSTRACT In this paper, the Moving Target Travelling Salesman Problem (MTTSP) is described. In MTTSP, several sites are required to be visited which are moving with constant velocity in different directions. The distance of the sites from origin, velocity and the angle of movement are known in advance. The goal is to find the fastest tour starting and ending at the origin which intercepts all the sites. The method implemented using genetic algorithm approach on the various data sets and the results are compared with greedy approach. General Terms Algorithm, complexity, Keywords Genetic Algorithm, Evolutionary Computation, Travelling Salesman Problem, Moving Target Travelling salesman problem, intercept, greedy method. 1. INTRODUCTION The traveling salesman problem (TSP) was originated by the studies of two mathematicians Sir William Rowam Hamilton from Ireland and Thomas Penyngton Kirkman from Briton in the 18th century. The general form of the TSP is believed to be studied further Kalr Menger in Vienna and promoted by Hassler, Whitney & Merrill at Princeton[2]. A detailed description about the connection between Menger & Whitney, and the development of the TSP can be found in Schrijver, 2005[3]. Given a set of cities and the cost of travel (or distance) between each possible pairs, the objective of the TSP is to find the best possible way of visiting all the cities and returning to the starting point that minimize the travel cost (or travel distance)[1]. Given