K
Kin Keung Lai
Researcher at Shenzhen University
Publications - 587
Citations - 15177
Kin Keung Lai is an academic researcher from Shenzhen University. The author has contributed to research in topics: Supply chain & Artificial neural network. The author has an hindex of 60, co-authored 547 publications receiving 13120 citations. Previous affiliations of Kin Keung Lai include City University of Hong Kong & North China Electric Power University.
Papers
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Journal ArticleDOI
Structural Analysis and Total Coal Demand Forecast in China
Qing Zhu,Qing Zhu,Zhongyu Zhang,Zhongyu Zhang,Rongyao Li,Kin Keung Lai,Shouyang Wang,Jian Chai,Jian Chai +8 more
TL;DR: In this article, a Bayesian vector autoregressive forecast model is constructed, with variables that include coal consumption, the gross value of industrial output, and the downstream industry output (cement, crude steel, and thermal power).
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Complex minimax programming under generalized convexity
TL;DR: In this paper, the Kuhn-Tucker-type sufficient optimality conditions for complex minimax programming under generalized invex functions were established, and two dual models were formulated to formulate weak, strong and strict converse duality theorems.
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A robust optimization solution to bottleneck generalized assignment problem under uncertainty
TL;DR: Two versions of bottleneck (or min–max) generalized assignment problem (BGAP) under capacity uncertainty are considered: Task–BGAP and Agent– BGAP and a robust optimization approach is employed.
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Optimality and duality for a nonsmooth multiobjective optimization involving generalized type I functions
TL;DR: A nonsmooth multiobjective optimization problem involving generalized (F, α, ρ, d)-type I function is considered and duality results are obtained for mixed type dual under the aforesaid assumptions.
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Low-Carbon Based Multi-Objective Bi-Level Power Dispatching under Uncertainty
TL;DR: In this paper, a hybrid uncertain multi-objective bi-level model with one leader and multiple followers is established to support the decision making of power dispatch and generation in low-carbon power dispatch problem under uncertainty.