Water wave optimization for the traveling salesman problem

Abstract

Water wave optimization (WWO) is a novel evolutionary algorithm borrowing ideas from shallow water wave models for global optimization problems. This paper presents a first study on WWO for a combinatorial optimization problem — the traveling salesman problem (TSP). We adapt the operators in the originalWWOso as to effectively exploring in a discrete solution space. The results of simulation experiments on a set of test instances from TSPLIB show that the proposed WWO algorithm is not only applicable and efficient for TSP, but also has significant performance advantage in comparison with two other methods, genetic algorithm (GA) and biogeography-based optimization (BBO).