Title :
Memetic algorithms and the molecular geometry optimization problem
Author_Institution :
Dept. of Phys., Ottawa Univ., Ont., Canada
Abstract :
A summary of recent work applying hybrid genetic algorithms to the molecular geometry optimization problem with the Lennard-Jones interaction is presented. The incorporation of local search optimizers has been critical to the success of these studies. A sample calculation employing a stochastic local search is presented to demonstrate its benefits
Keywords :
Lennard-Jones potential; genetic algorithms; geometry; molecular configurations; physics computing; search problems; stochastic processes; Lennard-Jones interaction; hybrid genetic algorithms; local search optimizers; memetic algorithms; molecular geometry optimization; stochastic local search; Chemistry; Evolutionary computation; Genetic algorithms; Genetic mutations; Geometry; Physics; Potential energy; Sequences; Stationary state; Stochastic processes;
Conference_Titel :
Evolutionary Computation, 2000. Proceedings of the 2000 Congress on
Conference_Location :
La Jolla, CA
Print_ISBN :
0-7803-6375-2
DOI :
10.1109/CEC.2000.870356
