Energy aware scheduling via tree-based search algorithms: A case study on lead plate curing

Energy consumption represents a significant part of production costs for many industrial processes. To ensure practical relevance, scheduling approaches must be capable of incorporating energy-related effects in their solutions. This paper models the energy-intensive production of lead-acid plates for batteries as a real-world scheduling problem. It further proposes a methodology that applies tree-based search algorithms to solve it. The described approach explicitly includes energy-related metrics in its optimization strategy. Both single- and multi-objective optimization strategies are employed, using processing time and energy consumption as evaluation metrics. The tree-based search strategies used include uninformed and informed strategies, such as beam and piloted-beam search. Experimental results on a constructed problem instance demonstrate that the proposed methods are capable of producing schedules that optimize both processing time and energy consumption. The approach allows balancing competing objectives, making it suitable for industrial settings where energy consumption represents a major cost factor.