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arXiv · 2309.16473

QUBO Resolution of the Job Reassignment Problem

Iñigo Perez Delgado·Beatriz García Markaida·Alejandro Mata Ali·Aitor Moreno Fdez. de Leceta
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Abstract

We present a subproblemation scheme for heuristical solving of the JSP (Job Reassignment Problem). The cost function of the JSP is described via a QUBO hamiltonian to allow implementation in both gate-based and annealing quantum computers. For a job pool of $K$ jobs, $\mathcal{O}(K^2)$ binary variables -- qubits -- are needed to solve the full problem, for a runtime of $\mathcal{O}(2^{K^2})$. With the presented heuristics, the average variable number of each of the $D$ subproblems to solve is $\mathcal{O}(K^2/2D)$, and the expected total runtime $\mathcal{O}(D2^{K^2/2D})$, achieving an exponential speedup.

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Iñigo Perez Delgado, Beatriz García Markaida, Alejandro Mata Ali, Aitor Moreno Fdez. de Leceta. 2023-09-28. QUBO Resolution of the Job Reassignment Problem. https://doi.org/10.1109/itsc57777.2023.10422467

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