DocumentCode
356794
Title
Memetic algorithms and the molecular geometry optimization problem
Author
Hodgson, R.J.W.
Author_Institution
Dept. of Phys., Ottawa Univ., Ont., Canada
Volume
1
fYear
2000
fDate
2000
Firstpage
625
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2000. Proceedings of the 2000 Congress on
Conference_Location
La Jolla, CA
Print_ISBN
0-7803-6375-2
Type
conf
DOI
10.1109/CEC.2000.870356
Filename
870356
Link To Document