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Titlebook: Global Optimization; Aimo Törn,Antanas Žilinskas Book 1989 Springer-Verlag Berlin Heidelberg 1989 Mathematica.STATISTICA.algorithms.optimi

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书目名称Global Optimization
编辑Aimo Törn,Antanas Žilinskas
视频video
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Global Optimization;  Aimo Törn,Antanas Žilinskas Book 1989 Springer-Verlag Berlin Heidelberg 1989 Mathematica.STATISTICA.algorithms.optimi
描述Global optimization is concerned with finding the global extremum (maximum or minimum) of a mathematically defined function (the objective function) in some region of interest. In many practical problems it is not known whether the objective function is unimodal in this region; in many cases it has proved to be multimodal. Unsophisticated use of local optimization techniques is normally inefficient for solving such problems. Therefore, more sophisticated methods designed for global optimization, i.e. global optimization methods, are important from a practical point of view. Most methods discussed here assume that the extremum is attained in the interior of the region of interest, i.e., that the problem is essentially unconstrained. Some methods address the general constrained problem. What is excluded is the treatment of methods designed for problems with a special structure, such as quadratic programming with negatively quadratic forms. This book is the first broad treatment of global optimization with an extensive bibliography covering research done both in east and west. Different ideas and methods proposed for global optimization are classified, described and discussed. The eff
出版日期Book 1989
关键词Mathematica; STATISTICA; algorithms; optimization; programming; complexity
版次1
doihttps://doi.org/10.1007/3-540-50871-6
isbn_softcover978-3-540-50871-7
isbn_ebook978-3-540-46103-6Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 1989
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0302-9743 unction) in some region of interest. In many practical problems it is not known whether the objective function is unimodal in this region; in many cases it has proved to be multimodal. Unsophisticated use of local optimization techniques is normally inefficient for solving such problems. Therefore,
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Methods of generalized descent,ry to define more precisely the class of functions to which the algorithms of the considered type may be efficiently applied. An important problem to be solved is how to ensure the numerical stability of the exploited local minimization algorithms when applied to flat functions.
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Clustering methods,lating the goal prescribed to the effort needed to achieve this goal can be used. Considerable theoretical progress has been made in this direction. The clustering approach to global optimization thus rests on a sound theoretical base which makes these methods attractive both from a practical and mathematical standpoint.
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Introduction to Accountancy and Financeithm and of auxiliary functions whose minimization gives conditions under which better local minima of .(·) may successively be found. The auxilary functions are constructed using the objective function and penalty functions..However, the auxilary functions normally become rather flat and are theref
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Kaushik Bhattacharya,Soumik Mukhopadhyayly combine global and local search..The clustering technique facilitate efficient representation of the information on the problem encountered in the solution process. The output from the process showing the evolution of clusters contains a lot of extra information hard to formalize, but of great im
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