Abstract
Particle Swarm Optimization (PSO) is popular in optimization problems for its quick convergence and simple realization. The topology of standard PSO is global-coupling and likely to stop at local optima rather than the global one. This paper analyses PSO topology with complex network theory and proposes two approaches to improve PSO performance. One improvement is PSO with regular network structure (RN-PSO) and another is PSO with random network structure (RD-PSO). Experiments and comparisons on various optimization problems show the effectiveness of both methods.
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Li, F., Guo, J. (2014). Topology Optimization of Particle Swarm Optimization. In: Tan, Y., Shi, Y., Coello, C.A.C. (eds) Advances in Swarm Intelligence. ICSI 2014. Lecture Notes in Computer Science, vol 8794. Springer, Cham. https://doi.org/10.1007/978-3-319-11857-4_16
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DOI: https://doi.org/10.1007/978-3-319-11857-4_16
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