Analysis of exploration and exploitation in evolutionary algorithms by ancestry trees

Authors:
Matej Crepinsek;Marjan Mernik;Shih-Hsi Liu
Affiliations:
Faculty of Electrical Engineering and Computer Science, University of Maribor, Smetanova 17, 2000 Maribor, Slovenia.;Faculty of Electrical Engineering and Computer Science, University of Maribor, Smetanova 17, 2000 Maribor, Slovenia.;Department of Computer Science, California State University, 2576 E. San Ramon, Fresno, USA
Venue:
International Journal of Innovative Computing and Applications
Year:
2011

Citing 13
Cited 4

Optimization of control parameters for genetic algorithms

IEEE Transactions on Systems, Man and Cybernetics
Genetic algorithms + data structures = evolution programs (3rd ed.)

Genetic algorithms + data structures = evolution programs (3rd ed.)
On evolutionary exploration and exploitation

Fundamenta Informaticae
Diversity-based selection pooling scheme in evolution strategies

Proceedings of the 2001 ACM symposium on Applied computing
An Investigation of Niche and Species Formation in Genetic Function Optimization

Proceedings of the 3rd International Conference on Genetic Algorithms
Diversity-Guided Evolutionary Algorithms

PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
Intelligent exploration for genetic algorithms: using self-organizing maps in evolutionary computation

GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Searching for diverse, cooperative populations with genetic algorithms

Evolutionary Computation
Forking genetic algorithms: Gas with search space division schemes

Evolutionary Computation
Parameter Setting in Evolutionary Algorithms

Parameter Setting in Evolutionary Algorithms
To explore or to exploit: An entropy-driven approach for evolutionary algorithms

International Journal of Knowledge-based and Intelligent Engineering Systems
Parameter control in evolutionary algorithms

IEEE Transactions on Evolutionary Computation
A general-purpose tunable landscape generator

IEEE Transactions on Evolutionary Computation

An empirical tool for analysing the collective behaviour of population-based algorithms

EvoApplications'12 Proceedings of the 2012t European conference on Applications of Evolutionary Computation
A note on teaching-learning-based optimization algorithm

Information Sciences: an International Journal
Exploration and exploitation in evolutionary algorithms: A survey

ACM Computing Surveys (CSUR)
A parameter control method of evolutionary algorithms using exploration and exploitation measures with a practical application for fitting Sovova's mass transfer model

Applied Soft Computing

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper introduces an ancestry tree-based approach for exploration and exploitation analysis. The approach introduces a data structure to record the evolution history of a population and a number of exploration and exploitation metrics. Such an approach not only provides insight of how and when the exploration and exploitation influence an evolution process, but also how the genetic structure of an individual is affected. It can be used to better understand inner working of an evolutionary algorithm or in evolutionary algorithm designing phase to develop suitable variation operators with good balance between exploration and exploitation. The approach is applied to the multi-objective 0/1 knapsack problem.