Chasing the Swarm: A Predator-Prey Approach to Function Optimisation



Abstract: In this paper we describe our approach to predator-prey optimisation, a form of particle swarm optimisation
where new particles called predators are introduced. The objective of predator-prey optimisation is to use predator
particles to help avoiding premature convergence to sub-optimal solutions in particle swarm optimisers. The swarm
particles (prey particles) are repelled by predators, which in turn are attracted to the best individuals in the swarm. The
resulting interactions make total convergence difficult to the swarm, maintaining diversity in the population. First
results of this new approach on several benchmark functions are presented and the performance of the algorithm is
compared to the performance of the standard particle swarm optimiser.


Particle swarm optimisation, Predator-prey optimisation


Evolutionary Optimization, PSO


Mendel 2002, June 2002

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Year 2009 : 1 citations

 M. Kathrada (2009). The flexi-PSO: Towards a more flexible particle swarm optimizer. OPSEARCH, Volume 46, Number 1, pp. 52-68, Springer 2009.

Year 2006 : 1 citations

 Cecília Di Chio, Extended particle swarm to simulate biology-like systems. Proceedings of the 1rst European Graduate Workshop on Evolutionary Computation (EvoPhD 2006), M. Giacobini and J. Van Hemert (Eds.), Budapest, Hungary, 10-12 April, 2006.

Year 2005 : 1 citations

 Salima Nabti, Souham Meshoul, and Mohamed Batouche, Predator Prey Optimizer for Unsupervised Clustering in Image Segmentation, International Arab Conference on Information Technology, ACIT'2005, December 6th- 8th, 2005, Al-Isra Private University, Jordan.