极小极大问题的生物地理学优化邻近点算法

doi:10.3969/j.issn.1001-2400.2016.05.016

Abstract

Abstract:

Concerning the discrete nonlinear minimax problems with the convex function as each of its components, a new method, called the biogeography based optimization-proximal point algorithm, is presented. By using maximum-entropy methods, the minimax problem is transformed into the unconstrained optimization problem of the smooth function. The algorithm employs the proximal point algorithm as the outer algorithm, and the biogeography based optimization as the internal algorithm. The proposed algorithm which resolves several minimax problems is global convergent. Preliminary numerical experiments show that the proposed algorithm is an effective algorithm for nonlinear minimax problems.

Key words: biogeography based optimization, evolutionary computation, minimax problems, proximal point algorithm

YANG Guoping;LIU Sanyang;ZHANG Jianke. Biogeography based optimization-proximal point algorithm for nonlinear minimax problems[J].Journal of Xidian University, 2016, 43(5): 88-92+182.

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Biogeography based optimization-proximal point algorithm for nonlinear minimax problems

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