A new shop scheduling approach in support of sustainable manufacturing

Abstract

Shop scheduling is a classic manufacturing decision-making problem. A new approach to scheduling that considers peak power load and energy consumption (and associated carbon footprint) in addition to cycle time is presented. A general multi-objective mixed-integer programming formulation is provided and examined using a simplified case study that considers the scheduling of a variety of components on two machines. The challenges of finding a solution to this scheduling problem are discussed, which motivates the need for specialized algorithms for these new scheduling problems. Computationally efficient algorithms that compute near-optimal solutions and optimal solutions under specific assumptions are examined.