A hybrid genetic algorithm for the minimum interconnection cut problem

Tang, Maolin & Pan, Shenchen (2013) A hybrid genetic algorithm for the minimum interconnection cut problem. In Proceedings of the 2013 IEEE Congress on Evolutionary Computation, IEEE, Cancún, México, pp. 3004-3011.

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In the real world there are many problems in network of networks (NoNs) that can be abstracted to a so-called minimum interconnection cut problem, which is fundamentally different from those classical minimum cut problems in graph theory. Thus, it is desirable to propose an efficient and effective algorithm for the minimum interconnection cut problem. In this paper we formulate the problem in graph theory, transform it into a multi-objective and multi-constraint combinatorial optimization problem, and propose a hybrid genetic algorithm (HGA) for the problem. The HGA is a penalty-based genetic algorithm (GA) that incorporates an effective heuristic procedure to locally optimize the individuals in the population of the GA. The HGA has been implemented and evaluated by experiments. Experimental results have shown that the HGA is effective and efficient.

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ID Code: 62009
Item Type: Conference Paper
Refereed: Yes
Keywords: Hybrid genetic algorithm, Minimum interconnection cut, Optimization
DOI: 10.1109/CEC.2013.6557935
ISBN: 9781479904532
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2013 IEEE
Deposited On: 22 Aug 2013 23:30
Last Modified: 26 Aug 2013 00:28

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