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Wen-Jun Zhang
Researcher at Tsinghua University
Publications - 18
Citations - 1493
Wen-Jun Zhang is an academic researcher from Tsinghua University. The author has contributed to research in topics: Particle swarm optimization & Multi-swarm optimization. The author has an hindex of 12, co-authored 18 publications receiving 1455 citations.
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Proceedings ArticleDOI
DEPSO: hybrid particle swarm with differential evolution operator
Wen-Jun Zhang,Xiao-Feng Xie +1 more
TL;DR: A hybrid particle swarm with differential evolution operator, termed DEPSO, which provide the bell-shaped mutations with consensus on the population diversity along with the evolution, while keeping the self-organized particle swarm dynamics, is proposed.
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A dissipative particle swarm optimization
TL;DR: In this article, a dissipative particle swarm optimization is developed according to the self-organization of dissipative structure, and negative entropy is introduced to construct an opening dissipative system that is far from equilibrium so as to drive the irreversible evolution process with better fitness.
Proceedings ArticleDOI
Dissipative particle swarm optimization
TL;DR: A dissipative particle swarm optimization is developed according to the self-organization of dissipative structure where the negative entropy is introduced to construct an opening dissipative system that is far-from-equilibrium so as to driving the irreversible evolution process with better fitness.
Proceedings ArticleDOI
Adaptive particle swarm optimization on individual level
TL;DR: An adaptive particle swarm optimization (PSO) on individual level, a replacement criterion, based on the diversity of fitness between the current particle and the best historical experience, is introduced to maintain the social attribution of swarm adaptively by taking off inactive particles.
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Handling boundary constraints for numerical optimization by particle swarm flying in periodic search space
TL;DR: In this paper, the authors analyzed the performance of particle swarm with periodic boundary handling and showed that the periodic mode is capable of improving the search performance significantly, by compared with that of conventional modes and other algorithms.