A Linearized Relaxing Algorithm for the Specific Nonlinear Optimization Problem

Mio Horai, Hideo Kobayashi and Takashi G. Nitta

Abstract and Applied Analysis, 2016, vol. 2016, 1-8

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.

Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlaaa:1304954

DOI: 10.1155/2016/1304954

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