Geodesic
A comparative performance analysis of genetic algorithms and the Metropolis algorithm in some problems of solid-state physics
Numerical methods and programming, Tome 8 (2007) no. 1, pp. 77-87.

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The application of genetic algorithms to the optimization problems of solid-state physics is considered. A genetic algorithm is described and compared with the Metropolis algorithm for the Ising model with the absolute value of atom spins equal to 1. Some basic questions arising when using the genetic algorithms in solid-state physics are discussed.
Keywords: genetic algorithms, Metropolis algorithm, Ising model, solid state physics, optimization. 
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     author = {T. V. Panchenko and Yu. Yu. Tarasevich},
     title = {A comparative performance analysis of genetic algorithms and the {Metropolis} algorithm in some problems of solid-state physics},
     journal = {Numerical methods and programming},
     pages = {77--87},
     publisher = {mathdoc},
     volume = {8},
     number = {1},
     year = {2007},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/VMP_2007_8_1_a9/}
}
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T. V. Panchenko; Yu. Yu. Tarasevich. A comparative performance analysis of genetic algorithms and the Metropolis algorithm in some problems of solid-state physics. Numerical methods and programming, Tome 8 (2007) no. 1, pp. 77-87. http://geodesic.mathdoc.fr/item/VMP_2007_8_1_a9/