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A genetic algorithms tutorial tool for numerical function optimisation

Authors:

E. K. Burke,

D. B. VarleyAuthors Info & Claims

ACM SIGCSE Bulletin, Volume 29, Issue 3

Pages 27 - 30

https://doi.org/10.1145/268809.268830

Published: 04 June 1997 Publication History

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Abstract

The field of Genetic Algorithms has grown into a huge area over the last few years. Genetic Algorithms are adaptive methods, which can be used to solve search and optimisation problems over a period of generations, based upon the principles of natural selection and survival of the fittest. This paper describes an innovative tool to introduce the basics of the subject of Genetic Algorithms called GAVIn (Genetic Algorithms Visual Interface). It focuses on the domain of numerical function optimisation problems as these form a good basis for learning and operator comparison. The other problem domains are too varied and problem dependent to form a general, robust learning tool.

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Information & Contributors

Information

Published In

ACM SIGCSE Bulletin Volume 29, Issue 3

Sept. 1997

143 pages

ISSN:0097-8418

DOI:10.1145/268809

Chairmen:
Lillian N. Cassel
National Science Foundation, Arlington, VA
,
Mats Daniels
Uppsala Univ. Sweden
,
Editors:
James E. Miller
Univ. of mississippi, Hattiesburg
,
Gordon Davies
Open Univ., Milton Keynes, England, UK

Issue’s Table of Contents

ITiCSE '97: Proceedings of the 2nd conference on Integrating technology into computer science education
June 1997
147 pages
ISBN:0897919238
DOI:10.1145/268819
Chairmen:
Lillian N. Cassel
National Science Foundation, Arlington, VA
,
Mats Daniels
Uppsala Univ. Sweden
,
Editors:
James E. Miller
Univ. of Southern Mississippi, Hattiesburg, MS
,
Gordon Davies
Open Univ., Milton Keynes, England, UK

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 04 June 1997

Published in SIGCSE Volume 29, Issue 3

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Cited By

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Wang XMajid MJamali M(2011)Multi-core implementation of F-16 flight surface control system using Genetic Algorithm based adaptive control algorithmProceedings of the 2011 IEEE National Aerospace and Electronics Conference (NAECON)10.1109/NAECON.2011.6183100(191-194)Online publication date: Jul-2011
https://doi.org/10.1109/NAECON.2011.6183100
Jin HChen RZheng HChen JCheng YYu YChen TLiu X(2023)Excitement Surfeited Turns to Errors: Deep Learning Testing Framework Based on Excitable NeuronsInformation Sciences10.1016/j.ins.2023.118936(118936)Online publication date: Apr-2023
https://doi.org/10.1016/j.ins.2023.118936
Montenegro de Barros GPereira VRoboredo M(2021)ELECTRE tree: a machine learning approach to infer ELECTRE Tri-B parametersData Technologies and Applications10.1108/DTA-10-2020-025655:4(586-608)Online publication date: 30-Mar-2021
https://doi.org/10.1108/DTA-10-2020-0256
Xu KZhang DAn JLiu LLiu LWang D(2021)GenExp: Multi-objective pruning for deep neural network based on genetic algorithmNeurocomputing10.1016/j.neucom.2021.04.022451(81-94)Online publication date: Sep-2021
https://doi.org/10.1016/j.neucom.2021.04.022
Wang YYuan CLiu W(2012)Cellular Differentiation Algorithm for High Dimensional Numerical Function OptimizationProceedings of the 2012 11th International Conference on Machine Learning and Applications - Volume 0110.1109/ICMLA.2012.54(276-280)Online publication date: 12-Dec-2012
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Gardner BSimon D(2009)Evolutionary algorithm sandboxProceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics10.5555/1732323.1732421(577-582)Online publication date: 11-Oct-2009
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Gardner BSimon D(2009)Evolutionary algorithm sandbox: A web-based graphical user interface for evolutionary algorithms2009 IEEE International Conference on Systems, Man and Cybernetics10.1109/ICSMC.2009.5346657(577-582)Online publication date: Oct-2009
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Nguyen TGordon-Brown LWheeler PPeterson J(2009)GA-SVM Based Framework for Time Series ForecastingProceedings of the 2009 Fifth International Conference on Natural Computation - Volume 0110.1109/ICNC.2009.292(493-498)Online publication date: 14-Aug-2009
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Nguyen TGordon-Brown LPeterson J(2008)The Optimal Rule Structure for Fuzzy Systems in Function Approximation by Hybrid Approach in Learning ProcessProceedings of the 2008 International Conference on Computational Intelligence for Modelling Control & Automation10.1109/CIMCA.2008.40(1211-1216)Online publication date: 10-Dec-2008
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