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- W1970214522 abstract "The global optimization of a mathematical model determines the best parameters such that a target or cost function is minimized. Optimization problems arise in almost all scientific disciplines (operations research, life sciences, etc.). Only in a few exceptional cases, these problems can be solved analytically-exactly, so in practice numerical routines based on approximations have to be used. The routines return a result -- a so-called candidate of a global minimum. Unfortunately, the question whether the candidate represents the optimal solution, often remains unanswered. This article presents a simple-to-use, statistical analysis that determines and assesses the quality of such a result. This information is valuable and important -- especially for practical application." @default.
- W1970214522 created "2016-06-24" @default.
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- W1970214522 creator A5079508774 @default.
- W1970214522 date "2014-09-01" @default.
- W1970214522 modified "2023-10-03" @default.
- W1970214522 title "Statistical Analysis on Global Optimization" @default.
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- W1970214522 doi "https://doi.org/10.1109/mcsi.2014.15" @default.
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