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.