Abstract
The current paper uses a real-life scenario from logistics to compare various forms of neighbourhood topologies within particle swarm optimization (PSO). Overall, gbest (all particles are connected with each other and change information) outperforms other well-known topologies, which is in contrast to some other results in the literature that associate gbest with premature convergence. However, the advantage of gbest is less pronounced on simpler versions of the application. This suggests a relationship between the complexity of instances from an identical class of problems and the effectiveness of PSO neighbourhood topologies.
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Günther, M., Nissen, V. (2009). A Comparison of Neighbourhood Topologies for Staff Scheduling with Particle Swarm Optimisation. In: Mertsching, B., Hund, M., Aziz, Z. (eds) KI 2009: Advances in Artificial Intelligence. KI 2009. Lecture Notes in Computer Science(), vol 5803. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04617-9_24
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DOI: https://doi.org/10.1007/978-3-642-04617-9_24
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