Multi-objective predictive control using discrete TS fuzzy systems and a modified dynamic neighborhood PSO

Thamallah, Ali; Sakly, Anis; M’Śahli, Faouzi

doi:10.1109/ssd.2015.7348178

Cited by 3 publications

(1 citation statement)

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“…(2) Neighborhood topology-based principle: In order to enhance the individuals' information communication and maintain the population diversity, lots of novel PSO variants based on researching on the particles in a neighborhood are proposed. Niche technique [14], dynamic neighborhood [15], neighborhood information sharing [16], and so on, they are widely used strategies for neighborhood topology. The advantage of this principle can balance the exploitation and exploration ability of PSO, which makes the optimization capacity of population better.…”

Section: Introductionmentioning

confidence: 99%

Team Collaboration Particle Swarm Optimization and Its Application on Reliability Optimization

Zheng¹,

Ma²,

Zhang³

et al. 2021

IJCIS

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Particle swarm optimization (PSO) tends to be premature convergence due to easily trapping into local suboptimal areas. In order to overcome the PSO's defects, the reasons causing the defects are analyzed and summarized as population diversity deficiency, insufficient information sharing, unbalance of exploitation and exploration, and single update strategy. On this basis, inspired by human team collaboration behavior, a team collaboration particle swarm optimization (TCPSO) is proposed. Diversified updates strategies, dynamic grouping strategy, selectivity vector, and decreasing and increasing inertia weight are designed in TCPSO to solve the defects' reasons and improve the optimization performance. Eight typical test functions have been used to evaluate and compare the performance of different PSO variants, and the results have been proven that the optimal results found by TCPSO are better compared with other PSO variants, which demonstrates the rationality and effectiveness of TCPSO. Finally, a real-world problem for reliability optimization are solved by five algorithms, and the results prove the convergence rate and stable optimization performance of TCPSO, TCPSO can provide better support for reliability optimization of complex system.

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Section: Introductionmentioning

confidence: 99%