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http://bura.brunel.ac.uk/handle/2438/5865
Title: | Triggered memory-based swarm optimization in dynamic environments |
Authors: | Wang, H Wang, X Yang, S |
Issue Date: | 2007 |
Publisher: | Springer-Verlag |
Citation: | EvoWorkshops 2007: Applications of Evolutionary Computing, 4448: 637 - 646, Jun 2007 |
Abstract: | In recent years, there has been an increasing concern from the evolutionary computation community on dynamic optimization problems since many real-world optimization problems are time-varying. In this paper, a triggered memory scheme is introduced into the particle swarm optimization to deal with dynamic environments. The triggered memory scheme enhances traditional memory scheme with a triggered memory generator. Experimental study over a benchmark dynamic problem shows that the triggered memory-based particle swarm optimization algorithm has stronger robustness and adaptability than traditional particle swarm optimization algorithms, both with and without traditional memory scheme, for dynamic optimization problems. |
Description: | This is a post-print version of this article - Copyright @ 2007 Springer-Verlag |
URI: | http://www.springerlink.com/content/968170487738v217/?p=08562be785674584af3c691b82591045&pi=1 http://bura.brunel.ac.uk/handle/2438/5865 |
DOI: | http://dx.doi.org/10.1007/978-3-540-71805-5_70 |
Appears in Collections: | Publications Computer Science Dept of Computer Science Research Papers |
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