Water flow-like algorithm improvement using K-opt local search

The water flow-like algorithm (wfa) is a relatively new metaheuristic algorithm,which has shown good solution for the travelling salesman problem (tsp) and is comparable to state of the art results. the basic wfa for tsp uses a 2-opt searching method to decide a water flow splitting decision. previous algorithms,such as the ant colony system for the tsp,has shown that using k-opt (k>2) improves the solution,but increases its complexity exponentially. therefore,this paper aims to present the performance of the wfa-tsp using 3-opt and 4-opt,respectively,compare them with the basic wfa-tsp using 2-opt and the state of the art algorithms. the algorithms are evaluated using 16 benchmarks tsp datasets. the experimental results show that the proposed wfa-tsp-4opt outperforms in solution quality compare with others,due to its capacity of more exploration and less convergence. © 2017 universiti putra malaysia press.