BRCE: bi-roles co-evolution for energy-efficient distributed heterogeneous permutation flow shop scheduling with flexible machine speed

Abstract Distributed manufacturing is the mainstream model to accelerate production. However, heterogeneous production environment makes engineer hard find optimal scheduling. This work investigates energy-efficient distributed permutation flow scheduling problem with flexible machine speed (DHPFSP-FMS) minimizing makespan and energy consumption simultaneously. In DHPFSP-FMS, local search misleads population falling into optima which reduces convergence diversity. To solve this problem, a bi-roles co-evolutionary algorithm proposed contains following improvements: First, global divided two swarms producer consumer balance computation. Second, three heuristic rules are designed get high-quality initialization population. Next, five problem-based strategies converging. Then, an efficient energy-saving strategy presented save energy. Finally, verify performance of algorithm, 22 instances generated based on Taillard benchmark, number numerical experiments adopted. The experiment results state that our superior state-of-arts more for DHPFSP-FMS.