Tracking differential evolution algorithms: an adaptive approach through multinomial distribution tracking with exponential forgetting

Authors:
Michael G. Epitropakis;Dimirtis K. Tasoulis;Nicos G. Pavlidis;Vassilis P. Plagianakos;Michael N. Vrahatis
Affiliations:
Computational Intelligence Laboratory, Department of Mathematics, University of Patras, Patras, Greece;Winton Capital Management, London, U.K.;Department of Management Science, Lancaster University, U.K.;Department of Computer Science and Biomedical Informatics, University of Central Greece, Lamia, Greece;Computational Intelligence Laboratory, Department of Mathematics, University of Patras, Patras, Greece
Venue:
SETN'12 Proceedings of the 7th Hellenic conference on Artificial Intelligence: theories and applications
Year:
2012

Citing 13
Cited 0

Identification of Time-Varying Processes

Identification of Time-Varying Processes
Differential Evolution – A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces

Journal of Global Optimization
Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)

Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
Differential evolution algorithm with strategy adaptation for global numerical optimization

IEEE Transactions on Evolutionary Computation
Differential evolution using a neighborhood-based mutation operator

IEEE Transactions on Evolutionary Computation
JADE: adaptive differential evolution with optional external archive

IEEE Transactions on Evolutionary Computation
λ-Perceptron: An adaptive classifier for data streams

Pattern Recognition
Adaptive strategy selection in differential evolution for numerical optimization: An empirical study

Information Sciences: an International Journal
Editorial scalability of evolutionary algorithms and other metaheuristics for large-scale continuous optimization problems

Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special Issue on scalability of evolutionary algorithms and other metaheuristics for large-scale continuous optimization problems
Self-Adapting Control Parameters in Differential Evolution: A Comparative Study on Numerical Benchmark Problems

IEEE Transactions on Evolutionary Computation
Opposition-Based Differential Evolution

IEEE Transactions on Evolutionary Computation
Differential Evolution: A Survey of the State-of-the-Art

IEEE Transactions on Evolutionary Computation
Enhancing Differential Evolution Utilizing Proximity-Based Mutation Operators

IEEE Transactions on Evolutionary Computation

Quantified Score

Hi-index	0.00

Visualization

Abstract

Several Differential Evolution variants with modified search dynamics have been recently proposed, to improve the performance of the method. This work borrows ideas from adaptive filter theory to develop an "online" algorithmic adaptation framework. The proposed framework is based on tracking the parameters of a multinomial distribution to reflect changes in the evolutionary process. As such, we design a multinomial distribution tracker to capture the successful evolution movements of three Differential Evolution algorithms, in an attempt to aggregate their characteristics and their search dynamics. Experimental results on ten benchmark functions and comparisons with five state-of-the-art algorithms indicate that the proposed framework is competitive and very promising.