A novel multi-objective discrete water wave optimization for solving multi-objective blocking flow-shop scheduling problem

The blocking flow-shop scheduling problem (BFSP) has been aroused general attention due to its broad industrial applications. However, most researches about it mainly focus on optimization of single objective. Multiple objectives are less considered simultaneously. Actually, in the practical production, the consideration of multiple objectives simultaneously could give more realistic solutions to the decision maker. Therefore, in this paper, we propose a novel multi-objective discrete water wave optimization (MODWWO) algorithm to solve a multi-objective BFSP (MOBFSP) that minimizes both makespan and total flow time. In the proposed algorithm, a decomposition-based initialization strategy is developed to generate a population with high quality and diversity. Then, a ranking-based propagation operator is designed to guide the global exploration and local exploitation of algorithm. Afterwards, a local intensification-based breaking operator is applied to improve the quality of the new created waves. Furthermore, a problem-specific refraction operator is incorporated to avoid being trapped in local optimum. The proposed algorithm is evaluated based on the benchmark instances, and compared with several state-of-the-art multi-objective scheduling optimization approaches. The comparison results show that the proposed MODWWO is a high-performing method for the considered MOBFSP. (C) 2018 Elsevier B.V. All rights reserved.