Abstract
A common way of solving satisfiability instances with quantum methods is to transform these instances into instances of QUBO. State-of-the-art transformations from MAX-3SAT to QUBO work by mapping clauses of a 3SAT formula associated with the MAX-3SAT instance to an instance of QUBO and combining the resulting QUBOs into a single QUBO instance representing the whole MAX-3SAT instance. As creating these transformations is currently done manually or via exhaustive search methods and is, therefore, algorithmically inefficient, we see potential for including search-based optimization. In this paper, we propose two methods of using evolutionary algorithms to create QUBO representations of MAX-3SAT problems automatically. We evaluate our created QUBOs on 500 and 1000-clause 3SAT formulae and find competitive performance to state-of-the-art baselines when using both classical and quantum annealing solvers.
Original language | English |
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Title of host publication | GECCO '24 Companion |
Subtitle of host publication | Proceedings of the Genetic and Evolutionary Computation Conference Companion |
Place of Publication | New York, NY |
Publisher | ACM |
Pages | 1984-1992 |
Number of pages | 9 |
ISBN (Electronic) | 979-8-4007-0495-6 |
DOIs | |
Publication status | Published - 2024 |
Event | 2024 Genetic and Evolutionary Computation Conference - Melbourne Convention and Exhibition Centre (MCEC), Melbourne, Australia Duration: 14 Jul 2024 → 18 Jul 2024 https://gecco-2024.sigevo.org/HomePage |
Conference
Conference | 2024 Genetic and Evolutionary Computation Conference |
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Abbreviated title | GECCO 2024 |
Country/Territory | Australia |
City | Melbourne |
Period | 14/07/24 → 18/07/24 |
Internet address |
Bibliographical note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-careOtherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Keywords
- (MAX)-3SAT
- combinatorial optimization
- evolutionary algorithm
- QUBO