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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/10371
Title: Minimizing Lennard-Jones potential using a real coded genetic algorithm and Particle Swarm Optimization
Authors: Deep, K.
Katiyar V.K.
Shashi
Published in: World Journal of Modelling and Simulation
Abstract: In this paper a recently developed real coded genetic algorithm called MI-LXPM of Deep et al. [8] and Particle Swarm Optimization (PSO) are applied to the challenging problem of finding the minimum energy configuration of a cluster of identical atoms interacting through the Lennard-Jones potential. Finding the global minimum of this function is very difficult because it has a large number of local minima, which grows exponentially with molecule size. Computational results for a cluster containing up to 15 atoms are obtained and presented. The obtained results show the remarkable performance of MI-LXPM as compared to PSO and to the earlier published results.
Citation: World Journal of Modelling and Simulation (2011), 7(4): 312-320
URI: http://repository.iitr.ac.in/handle/123456789/10371
Issue Date: 2011
Keywords: Atomic cluster
Genetic algorithm
Global optimization
Lennard-Jones potential
Particle swarm optimization
ISSN: 17467233
Author Scopus IDs: 8561208900
6603690424
8301540900
Author Affiliations: Deep, K., Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee 247667, India
Katiyar, V.K., Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee 247667, India
Shashi, Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee 247667, India
Corresponding Author: Deep, K.; Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee 247667, India; email: kusumfma@iitr.ernet.in
Appears in Collections:Journal Publications [MA]

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