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A cost benefit operator for efficient multi level genetic algorithm searches

Mitchell, George G., McMullin, Barry orcid logoORCID: 0000-0002-5789-2068 and Decraene, James (2007) A cost benefit operator for efficient multi level genetic algorithm searches. In: CEC 2007: IEEE Congress on Evolutionary Computation 2007, 25-28 September 2007, Singapore. ISBN 978-1-4244-1339-3

In this paper we present a novel cost benefit operator that assists multi level genetic algorithm searches. Through the use of the cost benefit operator, it is possible to dynamically constrain the search of the base level genetic algorithm, to suit the user’s requirements. Initially we review meta-evolutionary (multi-level genetic algorithm) approaches. We note that the current literature has abundant studies on meta-evolutionary GAs. However these approaches have not identified an efficient approach to termination of base GA search or a means to balance practical consideration such as quality of solution and the expense of computation. Our Quality time tradeoff operator (QTT) is user defined, and acts as a base level termination operator and also provides a fitness value for the meta-level GA. In this manner the amount of computation time spent on less encouraging configurations can be specified by the user. Our approach has been applied to a computationally intensive test problem which evaluates a large set of configuration settings for the base GAs. This approach should be applicable across a wide range of practical problems (e.g. routing, logistic and biomedical applications).
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Additional Information:Pages 1344-1350
Subjects:Computer Science > Artificial intelligence
Computer Science > Algorithms
Engineering > Artificial life
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering
Research Institutes and Centres > Research Institute for Networks and Communications Engineering (RINCE)
Published in: Proceedings of the IEEE Congress on Evolutionary Computation 2007. . Institute of Electrical and Electronics Engineers. ISBN 978-1-4244-1339-3
Publisher:Institute of Electrical and Electronics Engineers
Official URL:http://dx.doi.org/10.1109/CEC.2007.4424627
Copyright Information:©2007 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
ID Code:4608
Deposited On:17 Jun 2009 08:59 by James Decraene . Last Modified 01 Sep 2020 12:44

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