MGAC (Modified Genetic Algorithm for Crystals and Clusters)

JULIO C. FACELLI, VICTOR E. BAZTERRA AND MARTA B. FERRARO

CAMBRIDGE-INGLATERRA

Workshop; CSP2007; 2007

CAMBRIDGE CRYSTALLOGRAPHIC DATA CENTER

Genetic Algorithms (GAs) are a family of search techniques rooted on the ideas of Darwinian evolution.1, 2 Operators analogue to crossover, mutation and natural selection are employed to perform a search able to explore and learn the multidimensional parameter space and determine which regions of the space provide good solutions to a problem. To improve their convergence GAs are commonly coupled with local optimisations at each generation. This combined approach has been implemented in our program MGAC (Modified Genetic Algorithm for Crystal and Clusters).3-6