Abstract
This paper considers the problem of maximizing the total weighted number of on-time jobs on a single machine. Using the problem as a case study, we present a new approach to solving NP-hard discrete optimization problems using D-Wave’s QPU quantum processor architecture implementing quantum annealing. Although optimization on a quantum machine does not guarantee optimality, the hybrid method of construction of the partitioning and constraint algorithm proposed in this paper, using together CPU and QPU as well as Lagrange relaxation for upper bounds determination, makes it possible to determine the exact, optimal solution.
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Bożejko, W., Pempera, J., Uchroński, M., Wodecki, M. (2023). An Exact Quantum Annealing-Driven Branch and Bound Algorithm for Maximizing the Total Weighted Number of on-Time Jobs on a Single Machine. In: Pawelczyk, M., Bismor, D., Ogonowski, S., Kacprzyk, J. (eds) Advanced, Contemporary Control. PCC 2023. Lecture Notes in Networks and Systems, vol 709. Springer, Cham. https://doi.org/10.1007/978-3-031-35173-0_8
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DOI: https://doi.org/10.1007/978-3-031-35173-0_8
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