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Conference Paper

Evolutionary Algorithms for Cardinality-Constrained Ising Models

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Bhuva,  Vijay
Computer Science, University of Passau, Germany;
Thermodynamics and Kinetics of Defects, Computational Materials Design, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society;

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Huber,  Liam
Thermodynamics and Kinetics of Defects, Computational Materials Design, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society;

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Citation

Bhuva, V., Dang, D.-C., Huber, L., & Sudholt, D. (2022). Evolutionary Algorithms for Cardinality-Constrained Ising Models. In G. Rudolph, A. V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, & T. Tušar (Eds.), Parallel Problem Solving from Nature – PPSN XVII. PPSN 2022. Lecture Notes in Computer Science (pp. 456-469). doi:10.1007/978-3-031-14721-0_32.


Cite as: https://hdl.handle.net/21.11116/0000-000A-E307-E
Abstract
The Ising model is a famous model of ferromagnetism, in which atoms can have one of two spins and atoms that are neighboured prefer to have the same spin. Ising models have been studied in evolutionary computation due to their inherent symmetry that poses a challenge for evolutionary algorithms.