Improving molecular simulation: a meta optimisation of Monte Carlo parameters
- Resource Type
- Conference
- Authors
- Leblanc, B.; Lutton, E.; Braunschweig, B.; Toulhoat, H.
- Source
- Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546) Evolutionary computation Evolutionary Computation, 2001. Proceedings of the 2001 Congress on. 1:501-507 vol. 1 2001
- Subject
- Computing and Processing
Monte Carlo methods
Sampling methods
Computational modeling
Evolutionary computation
Polymers
Fractals
Genetics
Amorphous materials
Potential energy
Proteins
- Language
We present a new approach to performing molecular simulations using evolutionary algorithms. The main application is the simulation of dense amorphous polymers and the goal is to improve the efficiency of sampling, in other words to obtain valid samples from the phase state more rapidly. Our approach is based on parallel Markovian Monte Carlo simulations of the same physico-chemical system, where we optimise some Monte Carlo parameters by means of a real coded genetic algorithm.