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author:

Guo, W. (Guo, W..) [1] | Huang, Q. (Huang, Q..) [2] | Chen, G. (Chen, G..) [3] | Yu, L. (Yu, L..) [4]

Indexed by:

Scopus

Abstract:

From the computation point of view, task scheduling for distributed sensor network is an NPhard combinatorial optimization problem. The Particle Swarm Optimization (PSO) has been proved to be a good optimization algorithm with outstanding global performance. However, PSO cannot be directly used in the combinatorial optimization problem mentioned above due to its continuity. In this paper, a heuristic discrete PSO (HDPSO) with a well-designed particle position code is proposed, in which effective fitness function based on approximate optimal waiting approach is adopted. Experiments show that the performance of the proposed algorithm is better than genetic algorithm. © 2009 IEEE.

Keyword:

Community:

  • [ 1 ] [Guo, W.]College of Physics and Information Engineering, Fuzhou University, Fuzhou 350002, China
  • [ 2 ] [Guo, W.]College of Mathematics and Computer Science, Fuzhou University, Fuzhou 350002, China
  • [ 3 ] [Huang, Q.]College of Mathematics and Computer Science, Fuzhou University, Fuzhou 350002, China
  • [ 4 ] [Chen, G.]College of Mathematics and Computer Science, Fuzhou University, Fuzhou 350002, China
  • [ 5 ] [Yu, L.]College of Physics and Information Engineering, Fuzhou University, Fuzhou 350002, China

Reprint 's Address:

  • [Guo, W.]College of Physics and Information Engineering, Fuzhou University, Fuzhou 350002, China

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Source :

5th International Conference on Natural Computation, ICNC 2009

Year: 2009

Volume: 3

Page: 308-312

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 1

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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