An improved brain storm optimization algorithm for fuzzy distributed hybrid flowshop scheduling with setup time

The distributed hybrid flowshop scheduling (DHFS) problem, as one of the typical scheduling problems, has been researched in both academic and industrial fields during recent years. Consiering the DHFS with fuzzy processing time and setup time constraints, we develop an improved version of BSO, named IBSO. The objective is to minimize the maximize fuzzy completion time among all the factories. First, each solution is represented by a two-dimensional vectors. The two realistic constraints, i.e., the fuzzy processing time under uncertain enviornment and the setup time, make the problem close to the reality. Then, a novel constructive heuristic based on the Nawaz-Enscore-Ham (NEH) method, called distributed NEH, is proposed. Several local search heuristics considering the problem features and the objective are developed to enhance the local search abilities. Moreover a SA-based acceptance criterion is embeded to enhance the exploration abilities. Experimental results verify that the proposed algorithm is efficient and effective for solving the considered DHFS problems in comparison with other recently published efficient algorithms.