Energy-efficient scheduling for flexible flow shops by using MIP

In a response to the increasing demand for sustainable production together with the reduction in reserves of energy commodities, more and more manufacturers begin to pay attention to energy consumption problem during the production process. This paper looks at one of the potential approaches to improve energy efficiency during production which is to perform production scheduling with a combined manufacturing efficient and environmentally-friendly objective. Flexible flow shops are focused in this work and peak load is considered as the environment-related factor. Existing research has been mainly focusing on the general formulation or framework to integrate the energy reduction objective into the traditional scheduling problem. However, there still remains much room for improving the efficiency and adaptability. This paper builds an efficient discrete time Mixed Integer Programming (MIP) model, whose key idea is to reduce the number of binary integer variables. The major advantage of the proposed method is that a global optimal solution could be achieved without any compromise on computing efficiency. The applicability of the model has been validated through simulations and a comparison of discrete-time and continuous-time MIP formulations for this kind of problem is discussed.