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Title: Quantum and Digital Annealing for the Quadratic Assignment Problem
Authors: Codognet, Philippe
Diaz, Daniel
Abreu, Salvador
Issue Date: 2022
Publisher: IEEE Computer Society
Citation: P. Codognet, D. Diaz and S. Abreu, "Quantum and Digital Annealing for the Quadratic Assignment Problem," 2022 IEEE International Conference on Quantum Software (QSW), Barcelona, Spain, 2022, pp. 1-8, doi: 10.1109/QSW55613.2022.00016.
Abstract: The Quadratic Assignment Problem is a a classical constrained optimization problem used to model many real-life applications. We present experiments in solving the Quadratic Assignment Problem by means of Quantum Annealing and Quantum-inspired Annealing. We describe how to model this classical combinatorial problem in terms of QUBO (Quadratic Unconstrained Binary optimization) for implementing it on hardware solvers based on quantum or quantum-inspired annealing (D-Wave, Fujitsu Digital Annealing Unit and Fixstars Amplify Annealing Engine). We present performance result for these implementations and compare them with well established metaheuristic solvers on classical hardware, such as Robust Tabu Search and External Optimization.
Type: bookPart
Appears in Collections:NOVALINCS - Publicações - Capítulos de Livros

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