Work

QUBO Resolution of the Job Reassignment Problem

Year: 2023

Type: conference-paper

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.

Source: IEEE International Conference on Intelligent Transportation Systems (ITSC)

DOI: 10.1109/itsc57777.2023.10422467

Authors: Iñigo Perez Delgado, Beatriz García Markaida, Alejandro Mata Ali, Aitor Moreno Fdez de Leceta

Institutions: Euskadiko Parke Teknologikoa, Ibermática (Spain)

Language: English

Topic: Quantum Computing Algorithms and Architecture

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W4391768626

FWCI:

Cites: 7

Cited by:

Related to: 10