Title :
Monte Carlo simulation and population-based optimization
Author :
Cercueil, Alain ; François, Olivier
Author_Institution :
Lab. de Modelisation et Calcul, Inst. IMAG, Grenoble, France
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;
Conference_Titel :
Evolutionary Computation, 2001. Proceedings of the 2001 Congress on
Conference_Location :
Seoul
Print_ISBN :
0-7803-6657-3
DOI :
10.1109/CEC.2001.934389
