Energy-aware scheduling model and optimization for a flexible flow shop problem

Nowadays, manufacturing enterprises consumes a significant amount of energy; consequently, it has a significant potential to reduce resource consumption. However, key performance indicators of the traditional production do not completely take into account environmental impacts like energy consumption in production planning and scheduling. Against this background, an energy-aware scheduling model for a flexible flow shop problem is proposed. First, a mixed integer programming model based on energy savings is established to minimize energy consumption and makespan. Then, an improved heuristic algorithm, which combines genetic algorithm with simulated-annealing algorithm, is adopted to solve the mathematical model. Finally, a case study in a plant is tested. The experimental results show effectiveness of the model.