A genetic algorithm for the multi-source and multi-sink minimum vertex cut problem and its applications
| Data(s) |
29/05/2009
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| Resumo |
We present a new penalty-based genetic algorithm for the multi-source and multi-sink minimum vertex cut problem, and illustrate the algorithm’s usefulness with two real-world applications. It is proved in this paper that the genetic algorithm always produces a feasible solution by exploiting some domain-specific knowledge. The genetic algorithm has been implemented on the example applications and evaluated to show how well it scales as the problem size increases. |
| Formato |
application/pdf |
| Identificador | |
| Publicador |
IEEE |
| Relação |
http://eprints.qut.edu.au/27672/1/c27672.pdf DOI:10.1109/CEC.2009.4983353 Tang, Maolin & Fidge, Colin J. (2009) A genetic algorithm for the multi-source and multi-sink minimum vertex cut problem and its applications. In IEEE Congress on Evolutionary Computation, 18-21 May 2009, Nova Conference Centre and Cinema, Trondheim. http://purl.org/au-research/grants/ARC/LP0776344 |
| Direitos |
Copyright 2009 IEEE © 2009 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. |
| Fonte |
Faculty of Science and Technology; Information Security Institute |
| Palavras-Chave | #080100 ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING #genetic algorithm #minimal cut #optimization |
| Tipo |
Conference Paper |
