Abstract and Applied Analysis
- Abstr. Appl. Anal.
- Volume 2016 (2016), Article ID 1304954, 8 pages.
A Linearized Relaxing Algorithm for the Specific Nonlinear Optimization Problem
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.
Abstr. Appl. Anal., Volume 2016 (2016), Article ID 1304954, 8 pages.
Received: 27 December 2015
Accepted: 26 April 2016
First available in Project Euclid: 15 June 2016
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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