Solving the Traveling Salesman Problem Using Hydrological Cycle Algorithm

Abstract

In this paper, a recently developed nature-inspired optimization algorithm called the hydrological cycle algorithm (HCA) is evaluated on the traveling salesman problem (TSP). The HCA is based on the continuous movement of water drops in the natural hydrological cycle. The HCA performance is tested on various geometric structures and standard benchmarks instances. The HCA has successfully solved TSPs and obtained the optimal solution for 20 of 24 benchmarked instances, and near-optimal for the rest. The obtained results illustrate the efficiency of using HCA for solving discrete domain optimization problems. The solution quality and number of iterations were compared with those of other metaheuristic algorithms. The comparisons demonstrate the effectiveness of the HCA.

Water‐Based Metaheuristics: How Water Dynamics Can Help Us to Solve NP‐Hard Problems

“…HCA was introduced very recently in [48] and, to the best of our knowledge, it has only been used by its own authors so far. They have used it to solve the traveling salesman problem [49] and also to solve the capacitated vehicle routing problem [50]. Note that the method that differs the most from the others is WFA.…”

“…The pseudocode of HCA can be summarized as follows: [48] and, to the best of our knowledge, it has only been used by its own authors so far. They have used it to solve the traveling salesman problem [49] and also to solve the capacitated vehicle routing problem [50].…”