Title :
A genetic algorithm for the multi-source and multi-sink minimum vertex cut problem and its applications
Author :
Tang, M. ; Fidge, C.J.
Author_Institution :
Fac. of Sci. & Technol., Queensland Univ. of Technol., Brisbane, QLD
Abstract :
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.
Keywords :
directed graphs; genetic algorithms; minimisation; set theory; combinatorial optimization problem; multisink minimum vertex cut problem; multisource minimum vertex cut problem; penalty-based genetic algorithm; set theory; weighted directed graph; Algorithm design and analysis; Application software; Australia Council; Circuits; Genetic algorithms; Information analysis; Information security; Open source software; Software tools; Throughput;
Conference_Titel :
Evolutionary Computation, 2009. CEC '09. IEEE Congress on
Conference_Location :
Trondheim
Print_ISBN :
978-1-4244-2958-5
Electronic_ISBN :
978-1-4244-2959-2
DOI :
10.1109/CEC.2009.4983353
