Energy-aware flexible job shop scheduling under time-of-use pricing

Compromising productivity in exchange for energy-saving does not appeal to capital-intensive manufacturing industries. However, we might be able to maintain the same productivity while significantly reducing the energycost. This paper addresses a flexible job shop scheduling under time-of-use pricing and scheduled downtime aiming to minimize makespan and total energy cost. First, an integer linear programming model is proposed. Second, a constraint programming model is proposed. Third, a managerial insight is derived. The computational study demonstrates we can maintain the maximum productivity while significantly reducing the energy-cost by 6.9% on average in large-sized benchmark instances.

Automated summary

This paper investigates the minimization of energy cost and makespan in flexible job shop scheduling, proposing integer linear programming and constraint programming models. The computational study demonstrates that it is possible to maintain maximum productivity while significantly reducing energy cost in large-sized instances.