Haopeng Zhang
ABSTRACT
In this paper, inspired by speed-up and speed-down (SUSD) mechanism observed by the fish swarm avoiding light, an SUSD strategy is proposed to develop new swarm intelligence based optimization algorithms to enhance the accuracy and efficiency of swarm optimization algorithms. By comparing with the global best solution, each particle adaptively speeds up and speeds down towards the best solution. Specifically, a new directed speed term is added to the original particle swarm optimization (PSO) algorithm or other PSO variations. Due to the SUSD mechanism, the algorithm shows a great improvement of the accuracy and convergence rate compared with the original PSO and other PSO variations. The numerical evaluation is provided by solving recent benchmark functions in IEEE CEC 2013.
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Cross Ref
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- W. Wu, I. D. Couzin, and F. Zhang. Bio-inspired source seeking with no explicit gradient estimation. In Proc. IFAC Workshop on Distributed Estimation and Control in Networked Systems, pages 240--245, 2012.Google ScholarCross Ref
- H. Zhang and Q. Hui. Multiagent coordination optimization: A control-theoretic perspective of swarm intelligence algorithms. In 2013 IEEE Congr. Evolut. Comput., pages 3339--3346, Cancun, Mexico, 2013.Google ScholarCross Ref
Index Terms
- A speed-up and speed-down strategy for swarm optimization
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