Journal of Combinatorial Optimization

, Volume 35, Issue 4, pp 1261–1285 | Cite as

Quantile and mean value measures of search process complexity

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Abstract

Performance measures of metaheuristic algorithms assess the quality of a search process by statistically analysing its performance. Such criteria serve two purposes: they provide the verdict on which algorithm is better for what task, and they help applying an algorithm on a given task in the most effective way. The latter goal may be achieved by an appropriate restart strategy of the search process. Furthermore, these criteria are traditionally based on analysis of the search step mean value. Our aim is to elaborate the mean value analysis as well, but via a novel and more general quantile-based analytic approach, which can be used to define new measures. We prove and demonstrate this purpose on three quantile-based performance measures.

Keywords

Optimization Performance measure Time complexity Restart strategy Quantile Mean value 

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Software Engineering, Faculty of Nuclear Sciences and Physical EngineeringCzech Technical University in PraguePragueCzech Republic

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