An Improved Model for Parallel Machine Scheduling Under Time-of-Use Electricity Price

Junheng Cheng (1) , Feng Chu (2) , Mengchu Zhou (3)

1 School of Management
2 IBISC - Informatique, Biologie Intégrative et Systèmes Complexes
3 Institute of Systems Engineering

A recent study has led to an interesting mixed-integer linear programming (MILP) model for parallel machine scheduling under time-of-use (TOU) tariffs, which assumes great importance in achieving sustainable economic development. In this paper, we provide an improved MILP model by significantly reducing the number of decision variables. The computational results show that the performance of the improved model is superior to that of the existing one.

Domaines: Recherche opérationnelle [math.OC]

Junheng Cheng, Feng Chu, Mengchu Zhou. An Improved Model for Parallel Machine Scheduling Under Time-of-Use Electricity Price. IEEE Transactions on Automation Science and Engineering, 2018, 15 (2), pp.896--899. ⟨10.1109/TASE.2016.2631491⟩. ⟨hal-01455292⟩