Fast micro-differential evolution for topological active net optimization
Li, Yuan-Long and Zhan, Zhi-Hui and Gong, Yue-Jiao and Zhang, Jun and Li, Yun and Li, Qing (2016) Fast micro-differential evolution for topological active net optimization. IEEE Transactions on Cybernetics, 46 (6). pp. 1411-1423. ISSN 2168-2275 (https://doi.org/10.1109/TCYB.2015.2437282)
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Abstract
This paper studies the optimization problem of topological active net (TAN), which is often seen in image segmentation and shape modeling. A TAN is a topological structure containing many nodes, whose positions must be optimized while a predefined topology needs to be maintained. TAN optimization is often time-consuming and even constructing a single solution is hard to do. Such a problem is usually approached by a "best improvement local search" (BILS) algorithm based on deterministic search (DS), which is inefficient because it spends too much efforts in nonpromising probing. In this paper, we propose the use of micro-differential evolution (DE) to replace DS in BILS for improved directional guidance. The resultant algorithm is termed deBILS. Its micro-population efficiently utilizes historical information for potentially promising search directions and hence improves efficiency in probing. Results show that deBILS can probe promising neighborhoods for each node of a TAN. Experimental tests verify that deBILS offers substantially higher search speed and solution quality not only than ordinary BILS, but also the genetic algorithm and scatter search algorithm.
ORCID iDs
Li, Yuan-Long, Zhan, Zhi-Hui, Gong, Yue-Jiao, Zhang, Jun, Li, Yun ORCID: https://orcid.org/0000-0002-6575-1839 and Li, Qing;-
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Item type: Article ID code: 65162 Dates: DateEvent30 June 2016Published9 June 2015Published Online13 May 2015AcceptedNotes: © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Subjects: Technology > Electrical engineering. Electronics Nuclear engineering Department: Faculty of Engineering Depositing user: Pure Administrator Date deposited: 14 Aug 2018 14:06 Last modified: 11 Nov 2024 12:04 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/65162