A comparative performance analysis of genetic algorithms and the Metropolis algorithm in some problems of solid-state physics
Authors
-
T.V. Panchenko
-
Yu.Yu. Tarasevich
Keywords:
генетические алгоритмы
алгоритм Метрополиса
модель Изинга
физика твердого тела
оптимизация
Abstract
A difference scheme for computing gas flows is proposed. The scheme is based on an approximate non-iterative solution to the Riemann problem. A peculiarity of the scheme is the use of this solution in conservative variables, depending on the breakdown-waves velocities at single jumps. A choice of these velocities is discussed. Our approach ensures the absence of oscillations at gasdynamic jumps and allows one to avoid the difficulties caused by rarefaction zones when characteristics change their signs.
Section
Section 1. Numerical methods and applications
References
- Holland J.H. Adaptation in natural and artificial systems. Ann Arbor: University of Michigan Press, 1975.
- Michalewicz Z. Genetic algorithms + data structures = evolution programs. New York: Springer-Verlag, 1996.
- Mitchell M. An introduction to genetic algorithms. Cambridge: MIT Press, 1996.
- Fogel D.B. Evolutionary computation: towards a new philosophy of machine intelligence. Piscatway: IEEE Press, 1995.
- Koza J.R. Genetic programming. Cambridge: MIT Press, 1992.
- Hartmann A.K., Rieger H. Optimization algorithms in physics. Berlin: Wiley-VCH, 2002.
- Макконнелл Дж. Основы современных алгоритмов. М.: Техносфера, 2004.
- Батищев Д.И. Генетические алгоритмы решения экстремальных задач. Воронеж: Воронеж. гос. техн. ун-т, 1995.
- Поттер Д. Вычислительные методы в физике. М.: Мир, 1975.
- Metropolis N., Rosenbluth A.W., Rosenbluth M.N., Teller A.H., Teller E. Equation of state calculations by fast computing machines // J. Chem. Phys. 1953. 21, N 6. 1087-1092.
- Goldberg D. Genetic algorithms in search, optimization, and machine learning. Boston: Addison-Wesley, 1989.
- Курейчик В.А., Курейчик В.В., Гладков В.М. Генетические алгоритмы. М.: Физматлит, 2006.
- cSafak H., cSahin M., Gülveren B., Tomak M. Efficiency of genetic algorithm and determination of ground state energy of impurity in a spherical quantum dot // Int. J. of Modern Physics C. 2003. 14, N 6. 775-784.
- cSahin M., Tomak M. Self-consistent calculation of semiconductor heterojunctions by using quantum genetic algorithm // Int. J. of Modern Physics B. 2002. 16, N 26. 3883-3893.