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Is a comparison of results meaningful from the inexact replications of computational experiments?

Črepinšek, Matej and Liu, Shih-Hsi and Mernik, Luka and Mernik, Marjan (2016) Is a comparison of results meaningful from the inexact replications of computational experiments? Soft Computing, 20 (1). pp. 223-235. ISSN 1432-7643. http://resolver.caltech.edu/CaltechAUTHORS:20160128-150619917

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Abstract

The main objective of this paper is to correct the unreasonable and inaccurate criticism to our previous experiments using Teaching–Learning-Based Optimization algorithm and to quantify the amount of error that may arise due to incorrect counting of fitness evaluations. It is shown that inexact experiment replication should be avoided in comparisons between meta-heuristic algorithms whenever possible. Otherwise, an inexact replication and margin of error should be explicitly reported.


Item Type:Article
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1007/s00500-014-1493-4DOIArticle
http://link.springer.com/article/10.1007%2Fs00500-014-1493-4PublisherArticle
Additional Information:© 2016 Springer-Verlag Berlin Heidelberg. Published online: 1 November 2014. Communicated by V. Loia.
Subject Keywords:Teaching–learning-based optimization · Algorithm comparison · Replication of experiments
Record Number:CaltechAUTHORS:20160128-150619917
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20160128-150619917
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:64065
Collection:CaltechAUTHORS
Deposited By: Ruth Sustaita
Deposited On:28 Jan 2016 23:23
Last Modified:28 Jan 2016 23:23

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