A Survey of Advances in Landscape Analysis for Optimisation

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 computati...

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Vydáno v:Algorithms Ročník 14; číslo 2; s. 40
Hlavní autor: Malan, Katherine Mary
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 01.01.2021
Témata:
Algorithms
automated algorithm selection
Biological evolution
error landscape
Evolutionary algorithms
Evolutionary computation
Fitness
fitness landscape
landscape analysis
Machine learning
Neural networks
Optimization
Performance prediction
violation landscape
ISSN:1999-4893, 1999-4893
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Shrnutí: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.
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ISSN:1999-4893
1999-4893
DOI:10.3390/a14020040