A Multi-Start Iterated Local Search Algorithm for the Maximum Scatter Traveling Salesman Problem

Abstract

The maximum scatter traveling salesman problem (MSTSP) is a variant of the well-known traveling salesman problem (TSP) where the objective is to find a Hamiltonian cycle on a graph that maximizes the minimum length among its constituent edges. The MSTSP finds important application in manufacturing and medical imaging. In this study, we propose a multi-start iterated local search algorithm for the MSTSP. Two local search algorithms based on insertion and modified 2-opt moves have been developed as part of our approach. To investigate the performance of the proposed approach, benchmark instances from the standard TSPLIB are used. Computational results and their analysis show the effectiveness of the proposed approach.