Novel Approaches for Energy-Efficient Flexible Job-Shop Scheduling Problems
Rakovitis, Nikolaos
Li, Dan
Zhang, Nan
Li, Jie
Zhang, Liping
Xiao, Xin
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How to Cite

Rakovitis N., Li D., Zhang N., Li J., Zhang L., Xiao X., 2020, Novel Approaches for Energy-Efficient Flexible Job-Shop Scheduling Problems, Chemical Engineering Transactions, 81, 823-828.
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In this work, two novel mixed-integer linear programming models for energy efficient scheduling of flexible job-shops with simultaneous consideration of machine switching off-on strategy are developed. While the first model is based on the unit-specific event-based approach, the other one uses the sequence-based approach. The computational results demonstrate that the proposed models, especially the unit-specific event-based model, are more robust and efficient than the existing models. To solve industrial-scale problems efficiently, a hybrid algorithm is developed through the combination of the existing eGEP algorithm and mathematical programming approach. The hybrid algorithm leads to up to 15 % more energy savings in comparison to the eGEP algorithm.
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