Abstract and Applied Analysis

A Linearized Relaxing Algorithm for the Specific Nonlinear Optimization Problem

Mio Horai, Hideo Kobayashi, and Takashi G. Nitta

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Abstract

We propose a new method for the specific nonlinear and nonconvex global optimization problem by using a linear relaxation technique. To simplify the specific nonlinear and nonconvex optimization problem, we transform the problem to the lower linear relaxation form, and we solve the linear relaxation optimization problem by the Branch and Bound Algorithm. Under some reasonable assumptions, the global convergence of the algorithm is certified for the problem. Numerical results show that this method is more efficient than the previous methods.

Article information

Source
Abstr. Appl. Anal., Volume 2016 (2016), Article ID 1304954, 8 pages.

Dates
Received: 27 December 2015
Accepted: 26 April 2016
First available in Project Euclid: 15 June 2016

Permanent link to this document
https://projecteuclid.org/euclid.aaa/1465991977

Digital Object Identifier
doi:10.1155/2016/1304954

Mathematical Reviews number (MathSciNet)
MR3510922

Zentralblatt MATH identifier
06929340

Citation

Horai, Mio; Kobayashi, Hideo; Nitta, Takashi G. A Linearized Relaxing Algorithm for the Specific Nonlinear Optimization Problem. Abstr. Appl. Anal. 2016 (2016), Article ID 1304954, 8 pages. doi:10.1155/2016/1304954. https://projecteuclid.org/euclid.aaa/1465991977


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