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Open AccessArticle

A Quantum Adiabatic Algorithm for Multiobjective Combinatorial Optimization

Núcleo de Investigación y Desarrollo Tecnológico, Universidad Nacional de Asunción, San Lorenzo C.P. 2619, Paraguay
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This Paper is an Extended Version of Our Paper Pulished in Proceedings of the 42nd Latin American Conference on Informatics (CLEI), Valparaíso, Chile, 10–14 October 2016.
Axioms 2019, 8(1), 32; https://doi.org/10.3390/axioms8010032
Received: 14 November 2018 / Revised: 26 February 2019 / Accepted: 1 March 2019 / Published: 9 March 2019
(This article belongs to the Special Issue Foundations of Quantum Computing)
In this work we show how to use a quantum adiabatic algorithm to solve multiobjective optimization problems. For the first time, we demonstrate a theorem proving that the quantum adiabatic algorithm can find Pareto-optimal solutions in finite-time, provided some restrictions to the problem are met. A numerical example illustrates an application of the theorem to a well-known problem in multiobjective optimization. This result opens the door to solve multiobjective optimization problems using current technology based on quantum annealing. View Full-Text
Keywords: quantum computation; multiobjective optimization; quantum adiabatic evolution quantum computation; multiobjective optimization; quantum adiabatic evolution
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Barán, B.; Villagra, M. A Quantum Adiabatic Algorithm for Multiobjective Combinatorial Optimization. Axioms 2019, 8, 32.

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