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A fuzzy logic controller applied to a diversity-based multi-objective evolutionary algorithm for single-objective optimisation

Segredo, Eduardo; Segura, Carlos; León, Coromoto; Hart, Emma


Eduardo Segredo

Carlos Segura

Coromoto León


In recent years, Multi-Objective Evolutionary Algorithms (MOEAS) that consider diversity as an objective have been used to tackle single-objective optimisation prob- lems. The ability to deal with premature convergence has been greatly improved with these schemes. However, they usually increase the number of free parameters that need to be tuned. To improve results and avoid the tedious hand- tuning of algorithms, the use of automated parameter con- trol approaches that are able to adapt parameter values dur- ing the course of an evolutionary run are becoming more common in the field of Evolutionary Computation (EC). This research focuses on the application of parameter control approaches to diversity-based moeas. Two external parame- ter control methods are investigated; a novel method based on Fuzzy Logic and a recently proposed Hyper-heuristic. These are compared to an internal control method that uses self- adaptation. An extensive comparison of the three methods is carried out using a set of single-objective benchmark prob- lems of diverse complexity. Analyses include comparisons to a wide range of schemes with fixed parameters and to a single-objective approach. The results show that the fuzzy logic and hyper-heuristic methods are able to find similar or better solutions than the fixed parameter methods for a sig- nificant number of problems, with considerable savings in computational resources and time, whereas the self-adaptive strategy provides little benefit. Finally, we also demonstrate that the controlled diversity-based moea outperforms the single-objective scheme in most cases, thus showing the ben- efits of solving single-objective problems through diversity-based multi-objective schemes.

Journal Article Type Article
Acceptance Date Sep 14, 2014
Online Publication Date Sep 14, 2014
Publication Date 2015-10
Deposit Date Nov 27, 2014
Publicly Available Date May 15, 2017
Journal Soft Computing
Print ISSN 1432-7643
Electronic ISSN 1433-7479
Publisher BMC
Peer Reviewed Peer Reviewed
Volume 19
Issue 10
Pages 2927-2945
Keywords Parameter control, Fuzzy logic controllers, Hyper-heuristics, Self-adaptation, Diversity preservation, Benchmark problems
Public URL
Contract Date May 15, 2017


A fuzzy logic controller applied to a diversity-based multi-objective evolutionary algorithm for single-objective optimisation (accepted version) (1.5 Mb)

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