Order acceptance scheduling under Time-Of-Use and energy constraint

The present work addresses the issue of Order Acceptance Scheduling (OAS) problem on a single machine, incorporating periodic energy constraints and time-of-use (TOU) electricity pricing. The objective is to maximize net revenue by strategically selecting and scheduling orders while ensuring compliance with energy constraints and TOU pricing structures. This optimization process involves making informed decisions about order acceptance based on profitability, processing time, and energy requirements, while considering the cost fluctuations imposed by TOU pricing. To effectively address this problem, a time-indexed formulation is proposed that provides a structured approach to optimizing scheduling decisions under these constraints. In order to further enhance the performance of the proposed MILP model, two families of valid constraints have been developed. These developments have led to significant improvements in computational efficiency and solution quality.