Gradient gravitational search: An efficient metaheuristic algorithm for global optimization

The adaptation of novel techniques developed in the field of computational chemistry to solve the concerned problems for large and flexible molecules is taking the center stage with regard to efficient algorithm, computational cost and accuracy. In this article, the gradient‐based gravitational sear...

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Bibliographic Details
Published in:Journal of computational chemistry Vol. 36; no. 14; pp. 1060 - 1068
Main Authors: Dash, Tirtharaj, Sahu, Prabhat K.
Format: Journal Article
Language:English
Published: United States Blackwell Publishing Ltd 30.05.2015
Wiley Subscription Services, Inc
Subjects:
Accuracy
Chemistry
global optimization
gradient gravitational search
metaheuristic
Molecules
Optimization
Optimization algorithms
potential energy
protein folding
Simulation
metaheuristic
protein folding
potential energy
gradient gravitational search
global optimization
ISSN:0192-8651, 1096-987X, 1096-987X
Online Access:Get full text
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Summary:The adaptation of novel techniques developed in the field of computational chemistry to solve the concerned problems for large and flexible molecules is taking the center stage with regard to efficient algorithm, computational cost and accuracy. In this article, the gradient‐based gravitational search (GGS) algorithm, using analytical gradients for a fast minimization to the next local minimum has been reported. Its efficiency as metaheuristic approach has also been compared with Gradient Tabu Search and others like: Gravitational Search, Cuckoo Search, and Back Tracking Search algorithms for global optimization. Moreover, the GGS approach has also been applied to computational chemistry problems for finding the minimal value potential energy of two‐dimensional and three‐dimensional off‐lattice protein models. The simulation results reveal the relative stability and physical accuracy of protein models with efficient computational cost. © 2015 Wiley Periodicals, Inc. The adaptation of novel techniques developed in the field of computational chemistry to solve the concerned problems for large and flexible molecules is taking center stage with regard to efficient algorithms, computational cost, and accuracy. The gradient‐based gravitational search (GGS) algorithm, using analytical gradients for a fast minimization to the next local minimum, has been reported. The GGS approach has been applied to computational chemistry problems for finding the minimal value potential energy of two‐dimensional and three‐dimensional off‐lattice protein models.
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ISSN:0192-8651
1096-987X
1096-987X
DOI:10.1002/jcc.23891