Unlimited Budget Analysis

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Abstract

Performance analysis of randomised search heuristics is a rapidly growing and developing field. We contribute to its further development by introducing a novel analytical perspective that we call unlimited budget analysis. It has its roots in the very recently introduced approximation error analysis and bears some similarity to fixed budget analysis. The focus is on the progress an optimisation heuristic makes towards a set goal, not on the time it takes to reach this goal, setting it far apart from runtime analysis. We present the framework, apply it to simple mutation-based algorithms, covering both, local and global search. We provide analytical results for a number of simple example functions for unlimited budget analysis and compare them to results derived within the fixed budget framework for the same algorithms and functions.
Original languageEnglish
Title of host publicationGECCO 2019 Companion
Subtitle of host publicationProceedings of the 2019 Genetic and Evolutionary Computation Conference
PublisherAssociation for Computing Machinery
Pages427-428
Number of pages2
ISBN (Electronic)9781450367486
DOIs
Publication statusPublished - 13 Jul 2019
EventGECCO 2019: The Genetic and Evolutionary Computation Conference - Prague, Czech Republic
Duration: 13 Jul 201917 Jul 2019
https://gecco-2019.sigevo.org

Publication series

NameProceedings of the Genetic and Evolutionary Computation Conference

Conference

ConferenceGECCO 2019: The Genetic and Evolutionary Computation Conference
Country/TerritoryCzech Republic
CityPrague
Period13 Jul 201917 Jul 2019
Internet address

Keywords

  • Performance measures
  • Theory
  • Working principles of evolutionary computing

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