DocumentCode :
466067
Title :
Parallel Optimization Based on Generalized Cellular Automata
Author :
Shuai, Dianxun ; Xu, Li D. ; Zhang, Bin
Author_Institution :
East China Univ. of Sci. & Technol., Shanghai
Volume :
5
fYear :
2006
fDate :
8-11 Oct. 2006
Firstpage :
3804
Lastpage :
3809
Abstract :
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 Hopfleld-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.
Keywords :
cellular automata; computational complexity; computer networks; packet switching; travelling salesman problems; NP-hard problem; binary constraint matrix; computer networks; evolutionary dynamics; fast packet switching; generalized cellular automata; multigranularity macrocells; traveling salesman problem; Cellular neural networks; Cities and towns; Computer networks; Constraint optimization; Cybernetics; Hopfield neural networks; Neural networks; Packet switching; Throughput; Traveling salesman problems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man and Cybernetics, 2006. SMC '06. IEEE International Conference on
Conference_Location :
Taipei
Print_ISBN :
1-4244-0099-6
Electronic_ISBN :
1-4244-0100-3
Type :
conf
DOI :
10.1109/ICSMC.2006.384723
Filename :
4274488
Link To Document :
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