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Title: Using Scout Particles to Improve a Predator-Prey Optimizer
Authors: Silva, Arlindo
Neves, Ana
Gonçalves, Teresa
Keywords: particle swarm optimization
swarm intelligence
heterogeneous particle swarms
Issue Date: Apr-2013
Publisher: Springer Berlin Heidelberg
Citation: A. Silva, A. Neves, and T. Gon ̧calves. Using scout particles to improve a predator-prey optimizer. In ICANNGA’13 – Adaptive and Natural Computing Algorithms, volume 7824 of Lecture Notes in Computer Science, pages 130–139. Springer Berlin Heidelberg, April 2013. pdf.
Abstract: We discuss the use of scout particles, or scouts, to improve the performance of a new heterogeneous particle swarm optimization algorithm, called scouting predator-prey optimizer. Scout particles are proposed as a straightforward way of introducing new exploratory be- haviors into the swarm, expending minimal extra resources and without performing global modifications to the algorithm. Scouts are used both as general mechanisms to globally improve the algorithm and also as a sim- ple approach to taylor an algorithm to a problem by embodying specific knowledge. The role of each particle and the performance of the global algorithm is tested over a set of 10 benchmark functions and against two state-of-the-art evolutionary optimizers. The experimental results sug- gest that, with the addition of scout particles, the new optimizer can be competitive and even superior to the other algorithms, both in terms of performance and robustness.
Type: article
Appears in Collections:INF - Artigos em Livros de Actas/Proceedings

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