A Modified MOEA/D for Energy-efficient Flexible Job Shop Scheduling Problem

With the developing of green economy, energy-efficient scheduling has raised great interest recently. In our paper, we propose a modified multiobjective evolutionary algorithm based on decomposition (MMOEA/D) for the energy-efficient flexible job shop scheduling problem (EEFJSP) to optimize makespan and total energy consumption. A cooperative search operator is designed to improve the exploration. At the same time, a local intensification based on the properties of this problem is added to enhance the exploitation. Besides, the effect of parameter setting is investigated by the design-of experiment. Finally, comparison experiments are carried out between the MMOEA/D and the shuffled frog-leaping algorithm (SFLA). The results have shown that the MMOEA/D outperforms SFLA on this problem.