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第212行： − − The topology of the swarm defines the subset of particles with which each particle can exchange information.<ref name=kennedy2002population/> The basic version of the algorithm uses the global topology as the swarm communication structure.<ref name=bratton2007/> This topology allows all particles to communicate with all the other particles, thus the whole swarm share the same best position '''g''' from a single particle. However, this approach might lead the swarm to be trapped into a local minimum,<ref>Mendes, R. (2004). [https://pdfs.semanticscholar.org/d224/80b09d1f0759fb20e0fb0bd2de205457c8bc.pdf Population Topologies and Their Influence in Particle Swarm Performance] (PhD thesis). Universidade do Minho.</ref> thus different topologies have been used to control the flow of information among particles. For instance, in local topologies, particles only share information with a subset of particles.<ref name=bratton2007/> This subset can be a geometrical one<ref>Suganthan, Ponnuthurai N. "[https://ieeexplore.ieee.org/abstract/document/785514/ Particle swarm optimiser with neighbourhood operator]." Evolutionary Computation, 1999. CEC 99. Proceedings of the 1999 Congress on. Vol. 3. IEEE, 1999.</ref> – for example "the ''m'' nearest particles" – or, more often, a social one, i.e. a set of particles that is not depending on any distance. In such cases, the PSO variant is said to be local best (vs global best for the basic PSO). 第219行：
第217行： − − A commonly used swarm topology is the ring, in which each particle has just two neighbours, but there are many others.<ref name=bratton2007/> The topology is not necessarily static. In fact, since the topology is related to the diversity of communication of the particles,<ref name=oliveira2016communication/> some efforts have been done to create adaptive topologies (SPSO,<ref>SPSO [http://www.particleswarm.info Particle Swarm Central]</ref> APSO,<ref> Almasi, O. N. and Khooban, M. H. (2017). A parsimonious SVM model selection criterion for classification of real-world data sets via an adaptive population-based algorithm. Neural Computing and Applications, 1-9. [https://link.springer.com/article/10.1007/s00521-017-2930-y https://doi.org/10.1007/s00521-017-2930-y]</ref> stochastic star,<ref>Miranda, V., Keko, H. and Duque, Á. J. (2008). [https://repositorio.inesctec.pt/bitstream/123456789/1561/1/PS-05818.pdf Stochastic Star Communication Topology in Evolutionary Particle Swarms (EPSO)]. International Journal of Computational Intelligence Research (IJCIR), Volume 4, Number 2, pp. 105-116</ref> TRIBES,<ref>Clerc, M. (2006). Particle Swarm Optimization. ISTE (International Scientific and Technical Encyclopedia), 2006</ref> Cyber Swarm,<ref>Yin, P., Glover, F., Laguna, M., & Zhu, J. (2011). [http://leeds-faculty.colorado.edu/glover/fred%20pubs/428%20-%20A_complementary_cyber_swarm_algorithm_pub%20version%20w%20pen%20et%20al.pdf A Complementary Cyber Swarm Algorithm]. International Journal of Swarm Intelligence Research (IJSIR), 2(2), 22-41</ref> and C-PSO<ref name=elshamy07sis/>).
→Neighbourhoods and topologies
==Neighbourhoods and topologies==
==Neighbourhoods and topologies==
领域和拓扑结构<br>
领域和拓扑结构<br>
The topology of the swarm defines the subset of particles with which each particle can exchange information. thus different topologies have been used to control the flow of information among particles. For instance, in local topologies, particles only share information with a subset of particles. – for example "the m nearest particles" – or, more often, a social one, i.e. a set of particles that is not depending on any distance. In such cases, the PSO variant is said to be local best (vs global best for the basic PSO).
The topology of the swarm defines the subset of particles with which each particle can exchange information. thus different topologies have been used to control the flow of information among particles. For instance, in local topologies, particles only share information with a subset of particles. – for example "the m nearest particles" – or, more often, a social one, i.e. a set of particles that is not depending on any distance. In such cases, the PSO variant is said to be local best (vs global best for the basic PSO).
群体的拓扑结构定义了每个粒子可以交换信息的粒子子集。因此，不同的拓扑结构被用来控制粒子之间的信息流。例如，在局部拓扑结构中，粒子只与一部分粒子共享信息。- 例如“最接近的m个粒子”-或者更常见的是，一个社会群体，即一组不依赖于任何距离的粒子。在这种情况下，粒子群优化算法变种被认为是局部最优的(与基本的粒子群优化算法的全局最优相比)。
群体的拓扑结构定义了每个粒子可以交换信息的粒子子集。因此，不同的拓扑结构被用来控制粒子之间的信息流。例如，在局部拓扑结构中，粒子只与一部分粒子共享信息。- 例如“最接近的m个粒子”-或者更常见的是，一个社会群体，即一组不依赖于任何距离的粒子。在这种情况下，粒子群优化算法变种被认为是局部最优的(与基本的粒子群优化算法的全局最优相比)。
A commonly used swarm topology is the ring, in which each particle has just two neighbours, but there are many others. The topology is not necessarily static. In fact, since the topology is related to the diversity of communication of the particles, some efforts have been done to create adaptive topologies (SPSO, APSO, stochastic star, TRIBES, Cyber Swarm, and C-PSO).
A commonly used swarm topology is the ring, in which each particle has just two neighbours, but there are many others. The topology is not necessarily static. In fact, since the topology is related to the diversity of communication of the particles, some efforts have been done to create adaptive topologies (SPSO, APSO, stochastic star, TRIBES, Cyber Swarm, and C-PSO).