Design and Analysis of Optimization Algorithms Using Computational Statistics (Journal article)

Bartz Beielstein, T./ Parsopoulos, K. E./ Vrahatis, M. N.


We propose a highly flexible sequential methodology for the experimental analysis of optimization algorithms. The proposed technique employs computational statistic methods to investigate the interactions among optimization problems, algorithms, and environments. The workings of the proposed technique are illustrated on the parameterization and comparison of both a population based and a direct search algorithm, on a well known benchmark problem, as well as on a simplified model of a real world problem. Experimental results are reported and conclusions are derived. (© 2004 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)
Institution and School/Department of submitter: Πανεπιστήμιο Ιωαννίνων. Σχολή Θετικών Επιστημών. Τμήμα Μηχανικών Ηλεκτρονικών Υπολογιστών και Πληροφορικής
Keywords: Key word
URI: http://olympias.lib.uoi.gr/jspui/handle/123456789/10786
ISSN: 1611-8189
Publisher: WILEY-VCH Verlag
Appears in Collections:Άρθρα σε επιστημονικά περιοδικά ( Ανοικτά)




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