Evolutionary harmony search algorithm with Metropolis acceptance criterion for travelling salesman problem

Abstract

Harmony search HS algorithm is a new constructive meta-heuristic. In general, the intensification ability of a constructive meta-heuristic is not as good as that of iterative meta-heuristic, such as simulated annealing SA algorithm. To address this issue, we present a novel evolutionary HS EHS algorithm; in particular, we exploit the local search ability of SA algorithm to solve Travelling Salesman Problem TSP. In EHS, we combine the evolution idea from evolutionary computation EC and the Metropolis acceptance criterion of SA algorithm to improvise a new harmony. EHS algorithm can achieve significantly better intensification ability by taking advantage of the evolution process of EC and the local search ability from SA. Furthermore, the probabilistic accepting criterion of SA can effectively keep EHS from premature stagnation. Simulation experiments of EHS were conducted based on benchmark TSP problems, and the results show that EHS algorithm has demonstrated promising performance in terms of solution accuracy and CPU time.