Paper Info
Title
Ruggedness, Funnels And Gradients In Fitness Landscapes And The Effect On Pso Performance
Abstract
Fitness landscape analysis has focussed on many different aspects of optimisation problems such as ruggedness, neutrality, epistasis and evolvability. Although many techniques have been proposed, there are very few that have been shown to be practically useful as predictors of algorithm performance. This paper investigates three metrics related to the structure of fitness landscapes of continuous problems: a ruggedness measure based on entropy, a dispersion index measure for detecting the presence of funnels and a new proposed technique for estimating gradients. Results on a range of benchmark problems show that all proposed measures show some correlation to performance of a traditional particle swarm optimisation (PSO) algorithm on the same benchmark problems. The three metrics could therefore have value as part-predictors of PSO performance on unknown problems if used in conjunction with measures approximating other features that have been linked to problem difficulty for PSOs.
Year
DOI
Venue
2013
10.1109/CEC.2013.6557671
2013 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC)
Keywords
Field
DocType
benchmark testing,correlation,dispersion,accuracy,estimation,entropy,algorithm design and analysis,measurement
Particle swarm optimization,Mathematical optimization,Fitness landscape,Computer science,Evolvability,Epistasis,Artificial intelligence,Index of dispersion,Machine learning
Conference
Citations 
PageRank 
References 
13
0.64
11
Authors
2
Name
Order
Citations
PageRank
Katherine Malan116212.77
Andries Petrus Engelbrecht22183125.32