The role of crossover operator in the genetic optimization of magnetic models
The Ising model, introduced almost 100 years ago by Wilhelm Lenz and Ernst Ising, is the formalism still popular as a tool to describe magnetic properties of a wide class of materials. Among many issues which arise when using this model there exist problems related to the process of finding minimum...
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| Vydáno v: | Applied mathematics and computation Ročník 217; číslo 22; s. 9368 - 9379 |
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| Hlavní autor: | |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Amsterdam
Elsevier Inc
15.07.2011
Elsevier |
| Témata: | |
| ISSN: | 0096-3003, 1873-5649 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | The Ising model, introduced almost 100
years ago by Wilhelm Lenz and Ernst Ising, is the formalism still popular as a tool to describe magnetic properties of a wide class of materials. Among many issues which arise when using this model there exist problems related to the process of finding minimum energy of the system. Since these problems are NP-hard, optimizations can either be performed for some approximated cases or be the subject of global optimization techniques. In this paper we present an analysis of the effect of different crossover operators on the efficiency of genetic algorithm used to minimize energy in the Ising model. Although it is not a benchmark tool, we hope it may be interesting as a testing tool. |
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| Bibliografie: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 |
| ISSN: | 0096-3003 1873-5649 |
| DOI: | 10.1016/j.amc.2011.04.025 |