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.
Note to Practitioners -Time-of-use (TOU) pricing is widely implemented in many countries around the world, which provides variable electricity price over time. An appropriate response to the TOU policy can significantly reduce energy expense. This paper proposes an improved mixed-integer linear programming (MILP) approach for the parallel machine scheduling problem under TOU tariffs to minimize the total electricity cost based on a recently published model. The proposed approach can be easily implemented by using a commercial MILP solver such as IBM ILOG CPLEX. The optimal schedule could help decision makers reduce energy cost while maintaining high production efficiency.