Small world network based dynamic topology for particle swarm optimization
- Liu, Qingxue, Van Wyk, Barend Jacobus, Sun, Yanxia
- Authors: Liu, Qingxue , Van Wyk, Barend Jacobus , Sun, Yanxia
- Date: 2015
- Subjects: Particle swarm , Small world network , Neighborhood topology , Global model , Local model
- Language: English
- Type: Conference proceedings
- Identifier: http://hdl.handle.net/10210/22381 , uj:16196 , Citation: Liu, Q, Van Wyk, B.J. & Sun, Y. 2015. Small world network based dynamic topology for particle swarm optimization. 11th International Conference on Natural Computation (ICNC 2015). p. 289-294. ISBN: 978-1-4673-7678-5. DOI: 10.1109/ICNC.2015.7378005
- Description: Abstract: A new particle optimization algorithm with dynamic topology is proposed based on ‘small world’ network. The technique imitates the dissemination of information in a ‘small world network’ by dynamically updating the neighborhood topology of particle swarm optimization. The proposed dynamic neighborhood strategy can effectively coordinate the exploration and exploitation ability of particle swarm optimization. Simulations demonstrated that convergence of the swarms is guaranteed. Experiments demonstrated that the proposed method maintained the population diversity and enhanced the global search ability.
- Full Text:
- Authors: Liu, Qingxue , Van Wyk, Barend Jacobus , Sun, Yanxia
- Date: 2015
- Subjects: Particle swarm , Small world network , Neighborhood topology , Global model , Local model
- Language: English
- Type: Conference proceedings
- Identifier: http://hdl.handle.net/10210/22381 , uj:16196 , Citation: Liu, Q, Van Wyk, B.J. & Sun, Y. 2015. Small world network based dynamic topology for particle swarm optimization. 11th International Conference on Natural Computation (ICNC 2015). p. 289-294. ISBN: 978-1-4673-7678-5. DOI: 10.1109/ICNC.2015.7378005
- Description: Abstract: A new particle optimization algorithm with dynamic topology is proposed based on ‘small world’ network. The technique imitates the dissemination of information in a ‘small world network’ by dynamically updating the neighborhood topology of particle swarm optimization. The proposed dynamic neighborhood strategy can effectively coordinate the exploration and exploitation ability of particle swarm optimization. Simulations demonstrated that convergence of the swarms is guaranteed. Experiments demonstrated that the proposed method maintained the population diversity and enhanced the global search ability.
- Full Text:
Dynamic small world network topology for particle swarm optimization
- Liu, Qingxue, Van Wyk, Barend Jacobus, Du, Shengzhi, Sun, Yanxia
- Authors: Liu, Qingxue , Van Wyk, Barend Jacobus , Du, Shengzhi , Sun, Yanxia
- Date: 2016
- Subjects: Particle swarm optimization , Small world network , Dynamic neighbourhood topology
- Language: English
- Type: Article
- Identifier: http://hdl.handle.net/10210/124064 , uj:20869 , Citation: Liu, Q. et al. 2016. Dynamic small world network topology for particle swarm optimization.
- Description: Abstract: A new particle optimization algorithm with dynamic topology is proposed based on a small world network. The technique imitates the dissemination of information in a small world network by dynamically updating the neighborhood topology of the particle swarm optimization(PSO). In comparison with other four classic topologies and two PSO algorithms based on small world network, the proposed dynamic neighborhood strategy is more eÆective in coordinating the exploration and exploitation ability of PSO. Simulations demonstrated that the convergence of the swarms is faster than its competitors. Meanwhile, the proposed method maintains population diversity and enhances the global search ability for a series of benchmark problems.
- Full Text:
- Authors: Liu, Qingxue , Van Wyk, Barend Jacobus , Du, Shengzhi , Sun, Yanxia
- Date: 2016
- Subjects: Particle swarm optimization , Small world network , Dynamic neighbourhood topology
- Language: English
- Type: Article
- Identifier: http://hdl.handle.net/10210/124064 , uj:20869 , Citation: Liu, Q. et al. 2016. Dynamic small world network topology for particle swarm optimization.
- Description: Abstract: A new particle optimization algorithm with dynamic topology is proposed based on a small world network. The technique imitates the dissemination of information in a small world network by dynamically updating the neighborhood topology of the particle swarm optimization(PSO). In comparison with other four classic topologies and two PSO algorithms based on small world network, the proposed dynamic neighborhood strategy is more eÆective in coordinating the exploration and exploitation ability of PSO. Simulations demonstrated that the convergence of the swarms is faster than its competitors. Meanwhile, the proposed method maintains population diversity and enhances the global search ability for a series of benchmark problems.
- Full Text:
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