Hybridization of gradient descent algorithms with dynamic tunneling methods for global optimization

RoyChowdhury, Pinaki and Chansarkar, R. A. and Singh, Y. P. (2000) Hybridization of gradient descent algorithms with dynamic tunneling methods for global optimization. IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans, 30 (3). pp. 384-390. ISSN 1083-4427

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Abstract

An algorithm based on gradient descent techniques with dynamic tunneling methods for global optimization is proposed. The proposed algorithm consists of gradient descent fur local search and a direct search scheme, based on dynamic tunneling technique, for repelling away from local minimum to find the point of next local descent. This search process applied repeatedly finds the global minimum of an objective function. The convergence properties of the proposed algorithm is validated experimentally on benchmark problems. A comparative computational results confirm the importance of dynamic tunneling in gradient descent techniques.

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75.5-76.95 Electronic computers. Computer science
Divisions: Faculty of Computing and Informatics (FCI)
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 09 Sep 2011 02:30
Last Modified: 29 Oct 2013 07:39
URI: http://shdl.mmu.edu.my/id/eprint/2714

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