Effects of function translation and dimensionality reduction on landscape analysis

Mario Andres Munoz Acosta, Kate Amanda Smith-Miles

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

12 Citations (Scopus)


Exploratory Landscape Analysis (ELA) measures have been shown to predict algorithm performance; hence, they are being applied on critical tasks such as automatic algorithm selection and problem generation. This paper provides a cautionary examination on their use in black-box continuous optimization. We explore the effect that translations have on the measures, when the cost function is defined within a bound-constrained region. Furthermore, we examine the robustness of the neighborhood structure after dimensionality reduction. The results demonstrate that a measure may transition abruptly due a translation. Therefore, we should not generalize the measures of an instance nor report average values of a measure as belonging to the generating function. Moreover, dimensionality reduction could alter the neighborhood structure, such that the regions corresponding to significantly different functions overlap
Original languageEnglish
Title of host publication2015 IEEE Congress on Evolutionary Computation (CEC 2015)
EditorsTadahiko Murata
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages1336 - 1342
Number of pages7
ISBN (Print)9781479974924
Publication statusPublished - 2015
EventIEEE Congress on Evolutionary Computation 2015 - Sendai, Japan
Duration: 25 May 201528 May 2015
https://ieeexplore.ieee.org/xpl/conhome/7229815/proceeding (Proceedings)


ConferenceIEEE Congress on Evolutionary Computation 2015
Abbreviated titleIEEE CEC 2015
Internet address

Cite this