H
Henry Shu-Hung Chung
Researcher at City University of Hong Kong
Publications - 468
Citations - 17002
Henry Shu-Hung Chung is an academic researcher from City University of Hong Kong. The author has contributed to research in topics: Buck converter & Boost converter. The author has an hindex of 68, co-authored 446 publications receiving 15044 citations. Previous affiliations of Henry Shu-Hung Chung include University of Texas at Dallas & Aalborg University.
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Adaptive Particle Swarm Optimization
TL;DR: An adaptive particle swarm optimization that features better search efficiency than classical particle Swarm optimization (PSO) is presented and can perform a global search over the entire search space with faster convergence speed.
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Particle Swarm Optimization With an Aging Leader and Challengers
TL;DR: ALC-PSO is designed to overcome the problem of premature convergence without significantly impairing the fast-converging feature of PSO and serves as a challenging mechanism for promoting a suitable leader to lead the swarm.
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Cloud Computing Resource Scheduling and a Survey of Its Evolutionary Approaches
TL;DR: Through analyzing the cloud computing architecture, this survey first presents taxonomy at two levels of scheduling cloud resources, then paints a landscape of the scheduling problem and solutions, and a comprehensive survey of state-of-the-art approaches is presented systematically.
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Genetic Learning Particle Swarm Optimization
TL;DR: A specific novel *L-PSO algorithm is proposed, using genetic evolution to breed promising exemplars for PSO, and under such guidance, the global search ability and search efficiency of PSO are both enhanced.
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A Novel Set-Based Particle Swarm Optimization Method for Discrete Optimization Problems
TL;DR: A novel set-based PSO (S-PSO) method for the solutions of some combinatorial optimization problems (COPs) in discrete space is presented and tested on two famous COPs: the traveling salesman problem and the multidimensional knapsack problem.