Chen, StephenMontgomery, James2012-02-012012-02-012011Chen, S. & Montgomery, J. (2011). A simple strategy to maintain diversity and reduce crowding in particle swarm optimization. In D. Wang & M. Reynolds (Eds), AI 2011: Advances in artificial intelligence: Proceedings of the 24th Australasian Joint Conference in Artificial Intelligence, Perth, Australia, December 5-8, 2011 (pp. 281-290). Lecture Notes in Computer Science, 2011, Volume 7106/2011. Heidelberg: Springer978-3-642-25831-20302-9743http://hdl.handle.net/1885/8878Each particle in a swarm maintains its current position and its personal best position. It is useful to think of these personal best positions as a population of attractors -- updates to current positions are based on attractions to these personal best positions. If the population of attractors has high diversity, it will encourage a broad exploration of the search space with particles being drawn in many different directions. However, the population of attractors can converge quickly -- attractors can draw other particles towards them, and these particles can update their own personal bests to be near the first attractor. This convergence of attractors can be reduced by having a particle update the attractor it has approached rather than its own attractor/personal best. This simple change to the update procedure in particle swarm optimization incurs minimal computational cost, and it can lead to large performance improvements in multi-modal search spaces.10 pageshttp://www.springer.com/cda/content/document/cda_downloaddocument/copyrightlncs.pdf?SGWID=0-0-45-154182-p173621324 "Author may self-archive an author-created version of his/her Contribution on his/her own website and/or in his/her institutional repository, as well as on a non-commercial archival repository such as ArXiv/CoRR and HAL, including his/her final version. Author may also deposit this version on his/her funder’s or funder’s designated repository at the funder’s request or as a result of a legal obligation. Author may not use the publisher’s PDF version, which is posted on www.springerlink.com, for the purpose of self-archiving or deposit. Furthermore, Author may only post his/her version provided acknowledgement is given to the original source of publication and a link is inserted to the published article on Springer’s website. The link should be accompanied by the following text: "The original publication is available at www.springerlink.com". - from publisher web site (as at 01/02/12)particle swarm optimizationcrowdingnichingpopulation diversitymulti-modal search spaces201110.1007/978-3-642-25832-9_292015-12-09