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

Abstract

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.