Titlebook: Global Optimization; Aimo T?rn,Antanas ?ilinskas Book 1989 Springer-Verlag Berlin Heidelberg 1989 Mathematica.STATISTICA.algorithms.optimi

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書目名稱Global Optimization影響因子(影響力)




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書目名稱Global Optimization網(wǎng)絡公開度




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書目名稱Global Optimization被引頻次




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書目名稱Global Optimization年度引用




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書目名稱Global Optimization讀者反饋




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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