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Statistical analysis on global optimization

: Ullrich, Torsten; Fellner, Dieter W.


Institute of Electrical and Electronics Engineers -IEEE-:
International Conference on Mathematics and Computers in Sciences and in Industry, MCSI 2014. Proceedings : Varna, Bulgaria, 13 - 15 September 2014
Los Alamitos, Calif.: IEEE Computer Society Conference Publishing Services (CPS), 2014
ISBN: 978-1-4799-4744-7 (Print)
ISBN: 978-1-4799-4322-7
ISBN: 978-1-4799-4324-1
International Conference on Mathematics and Computers in Sciences and in Industry (MCSI) <2014, Varna>
Conference Paper
Fraunhofer IGD ()
numeric method; statistic; optimization; Business Field: Virtual engineering; Research Area: (Interactive) simulation (SIM); Forschungsgruppe Semantic Models, Immersive Systems (SMIS)

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.