SMOOTHED FUNCTIONALS AND CONSTRAINED STOCHASTIC-APPROXIMATION

作     者：KREIMER, J RUBINSTEIN, RY 

出 版 物：《SIAM JOURNAL ON NUMERICAL ANALYSIS》 (工业与应用数学会数值分析杂志)

年 卷 期：1988年第25卷第2期

页      面：470-487页

核心收录：

学科分类：07[理学] 070104[理学-应用数学] 0701[理学-数学] 

主　　题：90 60 Monte Carlo method multiextremal optimization nonconvex programming smoothing stochastic approximation stochastic optimization 

摘      要：The problem of finding an extremum for a nonconvex function under convex constraints is considered. The original nonconvex function is replaced by an auxiliary one, called a smoothed function, which possesses some nice properties. Operating with the smoothed function and the given convex constraints the global extremum of the original problem is found.