A Policy-Based Meta-Heuristic Algorithm for Energy-Aware Distributed No-Wait Flow-Shop Scheduling in Heterogeneous Factory Systems

In the face of environmental deterioration and global climate change, the concept of carbon neutrality and carbon peaking has gained prominence as a means to balance development and environmental preservation worldwide. Energy-aware scheduling is becoming the key scenario for environment conservation in manufacturing. This study focuses on addressing the energy-aware distributed no-wait flow-shop scheduling problem in a heterogeneous factory system (EDNWFSP-HFS) to minimize total energy consumption (TEC) and total tardiness (TTDs). A mixed-integer linear programming (MILP) model is formulated and a policy-based meta-heuristic algorithm (MHA-PG) is specifically designed to solve EDNWFSP-HFS. First, the optimal allocation rules based on random sequence (OAR-RS) are designed to initialize the population. Second, a policy-based method is employed to guide the algorithm toward making a better decision. Third, the energy-saving strategy considering specific knowledge of EDNWFSP-HFS is summarized to further optimize the feasible solution. Extensive simulations are conducted, comparing the performance of MHA-PG against several state-of-the-art algorithms. The results demonstrate that the proposed algorithm outperforms the competing approaches in solving EDNWFSP-HFS, indicating its superior performance and effectiveness.