A Metropolis algorithm combined with Hooke–Jeeves local search method applied to global optimization

A hybridization of a recently introduced Metropolis algorithm named the Particle Collision Algorithm (PCA) and the Hooke–Jeeves local search method is applied to a testbed of global optimization functions and to real-world chemical equilibrium nonlinear systems. The results obtained by this method,...

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Bibliographic Details
Published in:Applied mathematics and computation 2010-09, Vol.217 (2), p.843-853
Main Authors: Rios-Coelho, A.C., Sacco, W.F., Henderson, N.
Format: Article
Language:English
Subjects:
Algorithms
Calculus of variations and optimal control
Dynamical systems
Exact sciences and technology
Global optimization
Hooke–Jeeves method
Hybrid methods
Mathematical analysis
Mathematical models
Mathematics
Metaheuristics
Metropolis algorithms
Nonlinear algebraic and transcendental equations
Numerical analysis
Numerical analysis. Scientific computation
Numerical methods in mathematical programming, optimization and calculus of variations
Numerical methods in optimization and calculus of variations
Optimization
Particle collisions
Real functions
Sciences and techniques of general use
Search methods
State of the art
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Summary:A hybridization of a recently introduced Metropolis algorithm named the Particle Collision Algorithm (PCA) and the Hooke–Jeeves local search method is applied to a testbed of global optimization functions and to real-world chemical equilibrium nonlinear systems. The results obtained by this method, called HJPCA, are compared against those achieved by two state-of-the-art global optimization methods, C-GRASP and GLOBAL. HJPCA performs better than both algorithms, thus demonstrating its potential for other applications.
ISSN:0096-3003
1873-5649
DOI:10.1016/j.amc.2010.06.027