AMT-PSO: An Adaptive Magnification Transformation Based Particle Swarm Optimizer-Reference-Cited by-同舟云学术

AMT-PSO: An Adaptive Magnification Transformation Based Particle Swarm Optimizer

Published:2011 Issue:4 Volume:E94-D Page:786-797
ISSN:0916-8532
Container-title:IEICE Transactions on Information and Systems
language:en
Short-container-title:IEICE Trans. Inf. & Syst.

Author:

ZHANG Junqi¹,NI Lina²¹,XIE Chen¹,TAN Ying³,TANG Zheng¹⁴

Affiliation:

1. Department of Computer Science and Technology, the Key Laboratory of Embedded System and Service Computing, Ministry of Education; Tongji University

2. College of Info Sci & Engi, Shandong University of Science & Technology

3. Key Laboratory of Machine Perception, Ministry of Education; Department of Machine Intelligence, School of Electronics Engineering and Computer Science, Peking University

4. Department of Intellectual Information Systems Engineering, University of Toyama

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Artificial Intelligence,Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Hardware and Architecture,Software

Link

http://www.jstage.jst.go.jp/article/transinf/E94.D/4/E94.D_4_786/_pdf

Reference35 articles.

1. [1] C. Blum and A. Roli, “Metaheuristics in combinatorial optimization: Overview and conceptual comparison,” ACM Comput. Surv., vol.35, no.3, pp.268-308, 2003.

2. [2] F. Glover and G.A. Kochenberger, Handbook of metaheuristics, Kluwer, Boston, 2003.

3. [3] H.H. Hoos and T. Stutzle, Stochastic local search, Morgan Kaufmann, Elsevier, 2005.

4. A Unified View on Hybrid Metaheuristics

5. [5] J. Kennedy and R. Eberhart, “Particle swarm optimization,” Proc. IEEE International Conference on Neural Networks, pp.1942-1948, Perth, Australia, 1995.

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