Energy-Aware Blocking Hybrid Flow Shop Scheduling Problem with Sequence-depend Setup Times and Machine Speed Levels

The industry sector has the second largest energy demand after electricity generation. Given the high trend of energy prices, scarcity of its supply due to political instability and dependency on fossil fuels for its production makes energy the primary challenge for the manufacturing sector to stay competitive. Therefore, in addition to novel equipment technologies that use less energy, energy-efficient scheduling has also been a priority for manufacturing companies. In this study, the Hybrid Flowshop Scheduling Problem with Blocking Constraints and Sequence-Depend Setup Times (BHFS-SDST) is investigated for the minimization of makespan and total energy consumption (TEC). First, a novel bi-objective Mixed Integer Linear Programming (MILP) model is formulated and solved through augmented epsilon constraints. Then, a novel multi-objective approach based on Iterated Greedy meta-heuristic is developed for larger instances. Efficiency and the scalability of the proposed approaches are tested with small, medium, and large instances. Computational experiments show the effectiveness of developed methods in solving the BHFS-SDST problem.