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Article

A Survey of Advances in Landscape Analysis for Optimisation

Department of Decision Sciences, University of South Africa, Pretoria 0002, South Africa
Algorithms 2021, 14(2), 40; https://doi.org/10.3390/a14020040
Received: 30 November 2020 / Revised: 31 December 2020 / Accepted: 11 January 2021 / Published: 28 January 2021
Fitness landscapes were proposed in 1932 as an abstract notion for understanding biological evolution and were later used to explain evolutionary algorithm behaviour. The last ten years has seen the field of fitness landscape analysis develop from a largely theoretical idea in evolutionary computation to a practical tool applied in optimisation in general and more recently in machine learning. With this widened scope, new types of landscapes have emerged such as multiobjective landscapes, violation landscapes, dynamic and coupled landscapes and error landscapes. This survey is a follow-up from a 2013 survey on fitness landscapes and includes an additional 11 landscape analysis techniques. The paper also includes a survey on the applications of landscape analysis for understanding complex problems and explaining algorithm behaviour, as well as algorithm performance prediction and automated algorithm configuration and selection. The extensive use of landscape analysis in a broad range of areas highlights the wide applicability of the techniques and the paper discusses some opportunities for further research in this growing field. View Full-Text
Keywords: fitness landscape; landscape analysis; violation landscape; error landscape; automated algorithm selection fitness landscape; landscape analysis; violation landscape; error landscape; automated algorithm selection
MDPI and ACS Style

Malan, K.M. A Survey of Advances in Landscape Analysis for Optimisation. Algorithms 2021, 14, 40. https://doi.org/10.3390/a14020040

AMA Style

Malan KM. A Survey of Advances in Landscape Analysis for Optimisation. Algorithms. 2021; 14(2):40. https://doi.org/10.3390/a14020040

Chicago/Turabian Style

Malan, Katherine M. 2021. "A Survey of Advances in Landscape Analysis for Optimisation" Algorithms 14, no. 2: 40. https://doi.org/10.3390/a14020040

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