Parallel optimization based on generalized cellular automata

被引：0
|
作者：
Dianxun Shuai [1 ]
Li D. Xu [2 ]
Bin Zhang [1 ]
机构：
[1] E China Univ Sci & Technol, Dept Comp Sci & Engn, Shanghai 200237, Peoples R China
[2] Old Dominion Univ, Coll Business & Publ Adm, Norfolk, VA 23529 USA
来源：
2006 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-6, PROCEEDINGS | 2006年
关键词：
D O I：
10.1109/ICSMC.2006.384723
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
the fast packet switching (FPS) in computer networks. This paper further extends GCA to effectively solving a class of optimization problems subject to a binary constraint matrix, including the FPS problem and the traveling salesman problem (TSP) that is NP-hard. In contrast to Hopfield-type neural networks and cellular neural networks, the proposed GCA approach has the pyramid architecture and evolutionary dynamics related to multi-granularity macro-cells. This paper discusses the details regarding the dynamics and properties of the improved GCA.erms of the solution quality.
引用
收藏
页码：3804 / +
页数：2
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