Next Article in Journal
Functional Boundedness of Balleans: Coarse Versions of Compactness
Previous Article in Journal
A New Set Theory for Analysis
Previous Article in Special Issue
Doily as Subgeometry of a Set of Nonunimodular Free Cyclic Submodules
Article Menu

Export Article

Open AccessArticle
Axioms 2019, 8(1), 32;

A Quantum Adiabatic Algorithm for Multiobjective Combinatorial Optimization

Núcleo de Investigación y Desarrollo Tecnológico, Universidad Nacional de Asunción, San Lorenzo C.P. 2619, Paraguay
Author to whom correspondence should be addressed.
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.
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)
PDF [436 KB, uploaded 11 March 2019]


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

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Barán, B.; Villagra, M. A Quantum Adiabatic Algorithm for Multiobjective Combinatorial Optimization. Axioms 2019, 8, 32.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Axioms EISSN 2075-1680 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top