A Hybrid Estimation of Distribution Algorithm for the Minimal Switching Graph Problem

Tang, Maolin & Lau, Raymond Y. K. (2006) A Hybrid Estimation of Distribution Algorithm for the Minimal Switching Graph Problem. In International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce Vol-1 (CIMCA-IAWTIC'06), 28-30 November 2006, Vienna, Austria.

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Minimal Switching Graph (MSG) is a graphical model for the constrained via minimization problem—a combinatorial optimization problem in integrated circuit design automation. From a computational point of view, the problem is NP-complete. In this paper we present a new approach to the MSG problem using hybrid Estimation of Distribution Algorithms (EDAs). This approach uses a Univariate Marginal Distribution Algorithm (UMDA) to sample start search points and employs a hill-climbing algorithm to find a local optimum in the basins where the start search points are located. By making use of the efficient exploration of the UMDA and the effective exploitation of the hill-climbing algorithm, this hybrid EDA can find an optimal or nearoptimal solution efficiently and effectively. The hybrid EDA has been implemented and compared with the UMDA and the hill-climbing algorithm. Experimental results show that the hybrid EDA significantly outperforms both the UMDA and the hill-climbing algorithm.

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ID Code: 9412
Item Type: Conference Paper
Refereed: Yes
DOI: 10.1109/CIMCA.2005.1631347
ISBN: 076952504001
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Copyright Owner: Copyright 2006 IEEE
Copyright Statement: 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.
Deposited On: 11 Sep 2007 00:00
Last Modified: 29 Feb 2012 13:21

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