A water flow algorithm for optimization problems

Abstract

A novel natured-inspired algorithm, called the water flow algorithm (WFA), for solving optimization problems has been proposed. The algorithm is designed by simulating the hydrological cycle in meteorology and the erosion phenomenon in nature. Basic operators of this algorithm are based on the raindrop distribution simulation, the property of water flow always moving to lower positions, and the erosion process to overcome obstacles. In this thesis, our focus is on combinatorial optimization problems, such as flow shop scheduling problems, quadratic assignment problem, and vehicle routing problems. The WFA has been customized to solve these problems. Experimental results show that the WFA can obtain optimal or near-optimal solutions to these problems within reasonable computation time. The WFA has also been developed to solve the multi-objective flexible flow shop scheduling problem with intermediate buffers. In this algorithm, landscape analysis as well as evaporation and precipitation processes are integrated to solve the multi-objective scheduling problem. Experimental results demonstrate the efficiency and potential of the WFA for solving multi-objective scheduling problems.