Neighborhood topologies in fully informed and best-of-neighborhood particle swarms

By James Kennedy, Rui Mendes. IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews), 2003

330 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Molecular Biology, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/58056ee7c4e1a28a89619811f96b7ef01b1579f3

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Citations in the corpus

Particle Swarm Optimization: Basic Concepts, Variants and Applications in Power Systems (2008, background): “The honey bee colony is considered as an intelligent system that is composed of a large number of sim-pliﬁed units (particles).”
A review of population-based meta-heuristic algorithm (2013, background): “In topological structures, Kennedy and Mendes proposed a ring topological structure PSO (LPSO) [64] and a Von Neumann topological structure PSO (VPSO) [65] to enhance the performance in solving multimodal problems.”
Heterogeneous comprehensive learning particle swarm optimization with enhanced exploration and exploitation (2015, unknown): “Based on the ﬁ ndings in [8,10], a fully-informed PSO (FIPS) was proposed in which information from fully connected neighborhood was used [11] and different neighborhood topologies were studied in [12].”
Adaptive Particle Swarm Optimization (2008, methodology): “The LPSO with a ring topological structure and the von Neumann topological structure PSO (VPSO) have been proposed by Kennedy and Mendes [45], [46] to enhance the”
Orthogonal Learning Particle Swarm Optimization (2009, methodology): “In LPSO, a particle uses the best historical experience of the particle in its neighborhood which is defined by some topological structure, such as the ring structure, the pyramid structure, or the von Neumann structure [14]–[16].”
Particle swarm optimization algorithm: an overview (2017, methodology): “…updating (Nickabadi et al. 2011), various PSO local formulation to consider the best solution within a local topological particle neighborhood instead of the entire swarm (Kennedy and Mendes 2002, 2003; Mendes et al. 2004) and integrating the PSO with other heuristic algorithms (Chen et al. 2013).”
Defining a Standard for Particle Swarm Optimization (2007, result): “…showed inferior performance when compared to the global gbest model, or global topology, shown in Figure 1(a), but more recent research has revealed that lbest swarms return improved results across many standard problem sets when used in conjunction with other improvements to the algorithm [7].”
An effective and distributed particle swarm optimization algorithm for flexible job-shop scheduling problem (2015, background): “On the other hand, there are topologies based on a local neighborhood, called ring or lbest (Kennedy and Mendes 2003).”
A hierarchical particle swarm optimizer and its adaptive variant (2005, background): “In [14] and [24], several neighborhood topologies or " sociometries " have been examined for the PSO algorithm.”