A Hybrid Second-Order Method for Homogenous Polynomial Optimization over Unit Sphere

© 2017, Operations Research Society of China, Periodicals Agency of Shanghai University, Science Press, and Springer-Verlag Berlin Heidelberg.In this paper, we propose a hybrid second-order method for homogenous polynomial optimization over the unit sphere in which the new iterate is generated by em...

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Main Authors: Wang, Y., Zhou, Guanglu
Format: Journal Article
Published: Springer 2017
Online Access:http://hdl.handle.net/20.500.11937/52420
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author Wang, Y.
Zhou, Guanglu
author_facet Wang, Y.
Zhou, Guanglu
author_sort Wang, Y.
building Curtin Institutional Repository
collection Online Access
description © 2017, Operations Research Society of China, Periodicals Agency of Shanghai University, Science Press, and Springer-Verlag Berlin Heidelberg.In this paper, we propose a hybrid second-order method for homogenous polynomial optimization over the unit sphere in which the new iterate is generated by employing the second-order information of the objective function. To guarantee the convergence, we recall the shifted power method when the second-order method does not make an improvement to the objective function. As the Hessian of the objective function can easily be computed and no line search is involved in the second-order iterative step, the method is not time-consuming. Further, the new iterate is generated in a relatively larger region and thus the global maximum can be likely obtained. The given numerical experiments show the efficiency of the proposed method.
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institution Curtin University Malaysia
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spelling curtin-20.500.11937-524202017-09-13T15:39:22Z A Hybrid Second-Order Method for Homogenous Polynomial Optimization over Unit Sphere Wang, Y. Zhou, Guanglu © 2017, Operations Research Society of China, Periodicals Agency of Shanghai University, Science Press, and Springer-Verlag Berlin Heidelberg.In this paper, we propose a hybrid second-order method for homogenous polynomial optimization over the unit sphere in which the new iterate is generated by employing the second-order information of the objective function. To guarantee the convergence, we recall the shifted power method when the second-order method does not make an improvement to the objective function. As the Hessian of the objective function can easily be computed and no line search is involved in the second-order iterative step, the method is not time-consuming. Further, the new iterate is generated in a relatively larger region and thus the global maximum can be likely obtained. The given numerical experiments show the efficiency of the proposed method. 2017 Journal Article http://hdl.handle.net/20.500.11937/52420 10.1007/s40305-016-0148-9 Springer restricted
spellingShingle Wang, Y.
Zhou, Guanglu
A Hybrid Second-Order Method for Homogenous Polynomial Optimization over Unit Sphere
title A Hybrid Second-Order Method for Homogenous Polynomial Optimization over Unit Sphere
title_full A Hybrid Second-Order Method for Homogenous Polynomial Optimization over Unit Sphere
title_fullStr A Hybrid Second-Order Method for Homogenous Polynomial Optimization over Unit Sphere
title_full_unstemmed A Hybrid Second-Order Method for Homogenous Polynomial Optimization over Unit Sphere
title_short A Hybrid Second-Order Method for Homogenous Polynomial Optimization over Unit Sphere
title_sort hybrid second-order method for homogenous polynomial optimization over unit sphere
url http://hdl.handle.net/20.500.11937/52420