A novel water wave optimization based memetic algorithm for flow-shop scheduling

Xin Yun, Xiaoyi Feng, Xin Lyu, Shouyang Wang, Bo Liu

Abstract: Recently, Water Wave Optimization (WWO) has been presented as an optimization approach which takes inspiration from shallow wave model considering wind forcing, nonlinear wave interaction, and frictional dissipation. In contrast to WWO dedicated for continuous optimization problems, this paper extends WWO for solving combinatorial permutation flow-shop scheduling problem (PFSSP). In particular, three fundamental search operators in WWO, i.e., propagation, refraction, and breaking have been re-formulated to make WWO suitable for solving combinatorial optimization problem. To enhance the searching performance and efficiency, an improved NEH based algorithm has been applied. Simulation results based on well-known benchmarks and comparisons indicate the competitive advantage of the proposed WWO based memetic algorithm in which the global exploration and the local exploitation are well balanced, providing satisfactory solutions over the state-of-the-art (meta) heuristics such as genetic algorithm for PFSSP.