A simplified water wave optimization algorithm

Borrowing ideas from shallow water wave theory, water wave optimization (WWO) is a new evolutionary algorithm that uses three wave-inspired operators including propagation, refraction, and breaking for effectively exploring a high-dimensional solution space of an optimization problem. In this paper we develop a simplified version of WWO (SimWWO) by leaving out the refraction operator and introducing a population size reduction strategy to better balance exploration and exploitation, meanwhile partially compensate the weeding-out effect of the refraction operator. SimWWO is easier to implement, and computational experiments show that the overall performance of SimWWO is better than the original WWO on the CEC 2015 single-objective optimization test problems.