Optimization for energy-efficient flexible flow shop scheduling under time of use electricity tariffs

With the development of society and economy, the global energy problem has become increasingly critical. Methods for time of use electricity tariffs have been introduced to balance the demand for resource and increase the energy efficiency in manufacturing industry. The scheduling problem for flexible flow shop in the environment of TOU is studied in this paper. An energy consumption model of machine tools is established which involves the processing energy, standby energy and set-up energy for a detailed description of electricity cost in shop-floor. The Improved Strength Pareto Evolutionary Algorithm is employed in which a novel gene encoding considering processing sequence, machine tool and processing time simultaneously is proposed to obtain the Pareto Front of the makespan and electricity cost. A case study is presented and the result shows that the proposed method is applicable for trade-off of electricity cost and delivery time for the purpose of enhanced energy efficiency.