Abstract
We consider a variant of the job shop scheduling problem, which considers different operational states of the machines (such as off, ramp up, setup, processing, standby and ramp down) and time-dependent energy prices and aims at minimizing the energy consumption of the machines. We propose an integer programming formulation that uses binary variables to explicitly describe the non-operational periods of the machines and present a branch-and-price approach for its solution. Our computational experiments show that this approach outperforms the natural time-indexed formulation.
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Bley, A., Linß, A. (2020). Job Shop Scheduling with Flexible Energy Prices and Time Windows. In: Neufeld, J.S., Buscher, U., Lasch, R., Möst, D., Schönberger, J. (eds) Operations Research Proceedings 2019. Operations Research Proceedings. Springer, Cham. https://doi.org/10.1007/978-3-030-48439-2_25
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DOI: https://doi.org/10.1007/978-3-030-48439-2_25
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