Constrained optimization using a multipoint type chaotic Lagrangian method with a coupling structure

This article proposes a new constrained optimization method using a multipoint type chaotic Lagrangian method that utilizes chaotic search trajectories generated by Lagrangian gradient dynamics with a coupling structure. In the proposed method, multiple search points autonomously implement global se...

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Bibliographic Details
Published in:Engineering optimization 2013-03, Vol.45 (3), p.311-336
Main Authors: Okamoto, Takashi, Hirata, Hironori
Format: Article
Language:English
Subjects:
Benchmarking
Benchmarks
chaos
Chaos theory
constrained optimization
Constraints
coupled dynamics
Dynamics
global optimization
Joining
Lagrange multiplier
Lagrangian method
Optimization
Parameter optimization
Searching
Trajectories
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Summary:This article proposes a new constrained optimization method using a multipoint type chaotic Lagrangian method that utilizes chaotic search trajectories generated by Lagrangian gradient dynamics with a coupling structure. In the proposed method, multiple search points autonomously implement global search using the chaotic search trajectory generated by the coupled Lagrangian gradient dynamics. These points are advected to elite points (which are chosen by considering their objective function values and their feasibility) by the coupling in order to explore promising regions intensively. In this way, the proposed method successfully provides diversification and intensification for constrained optimization problems. The effectiveness of the proposed method is confirmed through application to various types of benchmark problem, including the coil spring design problem, the benchmark problems used in the special session on constrained real parameter optimization in CEC2006, and a high-dimensional and multi-peaked constrained optimization problem.
ISSN:0305-215X
1029-0273
DOI:10.1080/0305215X.2012.675060