Abstract
This paper investigates the use of boundary constraint handling mechanisms to prevent unwanted particle roaming behaviour in high dimensional spaces. The paper tests a range of strategies on a benchmark for large scale optimization. The empirical analysis shows that the hyperbolic strategy, which scales down a particle’s velocity as it approaches the boundary, performs statistically significantly better than the other methods considered in terms of the best objective function value achieved. The hyperbolic strategy directly addresses the velocity explosion, thereby preventing unwanted roaming.
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This work is based on the research supported by the National Research Foundation (NRF) of South Africa (Grant Number 46712). The opinions, findings and conclusions or recommendations expressed in this article is that of the author(s) alone, and not that of the NRF. The NRF accepts no liability whatsoever in this regard.
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Oldewage, E.T., Engelbrecht, A.P., Cleghorn, C.W. (2018). Boundary Constraint Handling Techniques for Particle Swarm Optimization in High Dimensional Problem Spaces. In: Dorigo, M., Birattari, M., Blum, C., Christensen, A., Reina, A., Trianni, V. (eds) Swarm Intelligence. ANTS 2018. Lecture Notes in Computer Science(), vol 11172. Springer, Cham. https://doi.org/10.1007/978-3-030-00533-7_27
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