loading
Documents

Research.Publish.Connect.

Paper

Paper Unlock

Authors: G. A. Papakostas 1 ; Y. S. Boutalis 1 ; D. A. Karras 2 and B. G. Mertzios 3

Affiliations: 1 Democritus University of Thrace, Greece ; 2 Chalkis Institute of Technology; Hellenic Open University, Greece ; 3 Thessaloniki Institute of Technolog, Greece

ISBN: 972-8865-29-5

Keyword(s): Genetic Algorithms, Diversity, Clustering.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Computational Intelligence ; Enterprise Information Systems ; Evolutionary Computation and Control ; Evolutionary Computing ; Genetic Algorithms ; Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Optimization Algorithms ; Soft Computing

Abstract: In this paper, a novel measure of the population diversity of a Genetic Algorithm (GA) is presented. Chromosomes diversity plays a major role for the successfully operation of a GA, since it describes the number of the different candidate solutions that the algorithm evaluates, in order to find the optimal one, in respect to a performance index, called objective function. In a well defined algorithm, the diversity of the current population should be measurable, in order to estimate the performance of the algorithm. The resulted observation, that is, the measuring of the diversity, can then be used to real-time adjust the factors that determine the chromosomes variety (Pc, Pm), during the execution of the GA. It is shown, that a simple chromosomes clustering into the search space, by using the well known k-means algorithm, can give a useful picture of the population’s distribution. Thus, by translating the problem of finding the best solution to a GA-based problem into an iterative clu stering process, and by using the scatter matrices (Sw, Sb), which describe completely the candidate’s solutions topology, one could define a novel formula that gives the population diversity of the algorithm. (More)

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 34.239.158.107

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
A. Papakostas G.; S. Boutalis Y.; A. Karras D.; G. Mertzios B. and (2005). AN EXPLORATION MEASURE OF THE DIVERSITY.In Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 972-8865-29-5, pages 260-265. DOI: 10.5220/0001161702600265

@conference{icinco05,
author={G. {A. Papakostas} and Y. {S. Boutalis} and D. {A. Karras} and B. {G. Mertzios}},
title={AN EXPLORATION MEASURE OF THE DIVERSITY},
booktitle={Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2005},
pages={260-265},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001161702600265},
isbn={972-8865-29-5},
}

TY - CONF

JO - Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - AN EXPLORATION MEASURE OF THE DIVERSITY
SN - 972-8865-29-5
AU - A. Papakostas, G.
AU - S. Boutalis, Y.
AU - A. Karras, D.
AU - G. Mertzios, B.
PY - 2005
SP - 260
EP - 265
DO - 10.5220/0001161702600265

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.