Energy-Efficient Flexible Flow Shop Scheduling Under Time-Of-Use Rates with Renewable Energy Sources

In response to climate change, industries strive to curtail energy consumption while maintaining production efficiency. Focused on time-dependent electricity prices, this paper addresses the scheduling challenge in a flexible flow shop machine environment. The goal is to minimize both makespan and total electricity costs in a grid-connected manufacturing setup with battery storage, solar power, and a strategic turn on/turn of machine approach. A multi-objective mixed-integer linear programming model is developed, employing the ϵ-constraint method to reveal the trade-of between objectives and present Pareto-front solutions. The ensuing experimental study allows for the validation of the model and identification of its limits.