Properties and numerical testing of a parallel global optimization algorithm

被引:0
|
作者
Marco Gaviano
Daniela Lera
机构
[1] University of Cagliari,Dipartimento di Matematica e Informatica
来源
Numerical Algorithms | 2012年 / 60卷
关键词
Random search; Global optimization; Parallel computing;
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中图分类号
学科分类号
摘要
In the framework of multistart and local search algorithms that find the global minimum of a real function f(x), \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$ x \in S\subseteq R^n$\end{document}, Gaviano et alias proposed a rule for deciding, as soon as a local minimum has been found, whether to perform or not a new local minimization. That rule was designed to minimize the average local computational cost \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$eval_1(\cdotp)$\end{document} required to move from the current local minimum to a new one. In this paper the expression of the cost \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$eval_2(\cdotp)$\end{document} of the entire process of getting a global minimum is found and investigated; it is shown that \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$eval_2(\cdotp)$\end{document} has among its components \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$eval_1(\cdotp)$\end{document} and can be only monotonically increasing or decreasing; that is, it exhibits the same property of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$eval_1(\cdotp)$\end{document}. Moreover, a counterexample is given that shows that the optimal values given by \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$eval_1(\cdotp)$\end{document} and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$eval_2(\cdotp)$\end{document} might not agree. Further, computational experiments of a parallel algorithm that uses the above rule are carried out in a MatLab environment.
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页码:613 / 629
页数:16
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