Solving symmetric eigenvalue problem via genetic algorithms: Serial versus parallel implementation

Authors:
Subhajit Nandy;Rahul Sharma;S. P. Bhattacharyya
Affiliations:
Andrew's High (H.S.) School, 33 Gariahat Road (South), Kolkata 700031, West Bengal, India;Department of Chemistry, St. Xavier's College, 30 Mother Teresa Sarani, Kolkata 700016, West Bengal, India;Department of Physical Chemistry, Indian Association for the Cultivation of Science, 2A and 2B Raja S. C. Mullick Road, Jadavpur, Kolkata 700032, West Bengal, India
Venue:
Applied Soft Computing
Year:
2011

Citing 19
Cited 0

Simulated annealing: theory and applications

Simulated annealing: theory and applications
Large-scale complex eigenvalue problems

Journal of Computational Physics
Neural networks for pattern recognition

Neural networks for pattern recognition
The symmetric eigenvalue problem

The symmetric eigenvalue problem
Genetic Algorithms in Search, Optimization and Machine Learning

Genetic Algorithms in Search, Optimization and Machine Learning
Neural Networks: A Comprehensive Foundation

Neural Networks: A Comprehensive Foundation
Fuzzy fixed charge solid transportation problem and algorithm

Applied Soft Computing
Optimal process design of two-stage multiple responses grinding processes using desirability functions and metaheuristic technique

Applied Soft Computing
Advances on protein folding simulations based on the lattice HP models with natural computing

Applied Soft Computing
Wavelet based fault detection in analog VLSI circuits using neural networks

Applied Soft Computing
MAkE: Multiobjective algorithm for k-way equipartitioning of a point set

Applied Soft Computing
A dynamic programming approach for finding shortest chains in a fuzzy network

Applied Soft Computing
Multicriteria decisions on interdependent infrastructure transportation projects using an evolutionary-based framework

Applied Soft Computing
A solid transportation problem for an item with fixed charge, vechicle cost and price discounted varying charge using genetic algorithm

Applied Soft Computing
Genetic programming for QSAR investigation of docking energy

Applied Soft Computing
The SR-GCWS hybrid algorithm for solving the capacitated vehicle routing problem

Applied Soft Computing
Fusion of soft computing and hard computing for large-scale plants: a general model

Applied Soft Computing
Simplifying Particle Swarm Optimization

Applied Soft Computing
Data mining with an ant colony optimization algorithm

IEEE Transactions on Evolutionary Computation

Quantified Score

Hi-index	0.00

Visualization

Abstract

Abstract: We propose a new method for computing more than one eigenvalue of small and medium sized real symmetric matrices simultaneously by minimizing a suitably defined average Rayleigh Quotient (@r"a"v) for the targeted group of eigenvalues by Genetic Algorithm. The proposed method is tested on two benchmark matrices of varying dimensions. Performance statistics is presented both as functions of dimensions of the matrices and as functions of the number of eigenvalues being sought simultaneously. A comparison is made with sequential search for multiple eigenvalues by minimization of Rayleigh Quotient with successive projections of unwanted eigenvectors. Parallel implementation of the algorithm shows an edge over its serial counterpart when larger number of eigenvalues are sought simultaneously and the dimensions of the matrices are higher.