SAPPO: A Simple, Adaptable, Predator Prey Optimiser

Abstract

The balance of exploration and exploitation in particle swarm optimisation is closely related to the choice of the algorithm's parameters. Achieving the right balance is essential for the success of a given optimisation task. This choice is a difficult task, since for different functions being optimised the ideal parameter sets can also bee very different. In this paper we try to deal with this issue by introducing two new mechanisms in the basic particle swarm optimiser: a predator-prey strategy to help maintain diversity in the swarm and a symbiosis based adaptive scheme to allow the co-evolution of the algorithm parameters and the parameters of the function being optimised. © Springer-Verlag Berlin Heidelberg 2003.