DocumentCode
1747739
Title
Monte Carlo simulation and population-based optimization
Author
Cercueil, Alain ; François, Olivier
Author_Institution
Lab. de Modelisation et Calcul, Inst. IMAG, Grenoble, France
Volume
1
fYear
2001
fDate
2001
Firstpage
191
Abstract
This paper briefly reviews some properties of Monte Carlo simulation and emphasizes the link to evolutionary computation. It shows how this connection can help to study evolutionary algorithms within a unified framework. It also gives some practical examples of implementation inspired from MOSES (the mutation-or-selection evolution strategy)
Keywords
Monte Carlo methods; evolutionary computation; optimisation; Monte Carlo simulation; evolutionary algorithms; evolutionary computation; mutation-or-selection evolution strategy; population-based optimization; unified framework; Boltzmann distribution; Computational modeling; Convergence; Cost function; Evolutionary computation; Markov random fields; Optimization methods; Probability distribution; Proportional control; Temperature distribution;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2001. Proceedings of the 2001 Congress on
Conference_Location
Seoul
Print_ISBN
0-7803-6657-3
Type
conf
DOI
10.1109/CEC.2001.934389
Filename
934389
Link To Document