An efficient mixed integer linear programming model for energy-conscious single machine scheduling under time-of-use tariffs

This paper investigates an energy-conscious single machine scheduling problem to minimize total electricity cost under the time-of-use (TOU) electricity pricing scheme. In such a scheme, the electricity consumed in different periods of a day requires different prices. Each job to be processed on the machine is characterized by their processing time and electricity consumption per hour. The objective is to arrange the processing of the jobs under TOU electricity tariffs so as to minimize the total electricity cost. An improved mix-integer linear programming model with less number of constraints is formulated for the problem. Computational results demonstrate that our model can solve the problem more effectively.