The enhanced best performance algorithm for the travelling salesman problem

Abstract

The Travelling Salesman Problem (TSP) is a largely studied discrete optimization problem, which is-Hard. This study compares the performances of three local search metaheuristic algorithms, in determining solutions to seven benchmark instances of symmetric TSP's. The algorithms investigated include the enhanced Best Performance Algorithm (eBPA), Tabu Search (TS) and Simulated Annealing (SA). This study is the first on the eBPA for the TSP. eBPA is a newly introduced metaheuristic in the literature. The results demonstrate the effectiveness of eBPA as an alternative optimization technique for difficult optimization problems.