Solving nonlinearly constrained global optimization problem via an auxiliary function method

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摘要

This paper considers the nonlinearly constrained continuous global minimization problem. Based on the idea of the penalty function method, an auxiliary function, which has approximately the same global minimizers as the original problem, is constructed. An algorithm is developed to minimize the auxiliary function to find an approximate constrained global minimizer of the constrained global minimization problem. The algorithm can escape from the previously converged local minimizers, and can converge to an approximate global minimizer of the problem asymptotically with probability one. Numerical experiments show that it is better than some other well known recent methods for constrained global minimization problems.

论文关键词:Nonlinearly constrained global minimization problem,Auxiliary function method,Convergence

论文评审过程:Received 3 July 2008, Revised 20 September 2008, Available online 6 January 2009.

论文官网地址:https://doi.org/10.1016/j.cam.2008.12.017