4 papers
Sparse Convex Quantile Regression: A Generalized Benders Decomposition Approach
Xiaoyu Luo, Chuanhou Gao
We develop a scalable algorithmic framework for sparse convex quantile regression (SCQR), addressing key computational challenges in the literature. Enhancing the classical CQR mod…
Learn to formulate: A surrogate model framework for generalized assignment problem with routing constraints
Sen Xue, Chuanhou Gao
The generalized assignment problem with routing constraints, e.g. the vehicle routing problem, has essential practical relevance. This paper focuses on addressing the complexities…
Lagrangian cuts generated by batch to efficiently solve two-stage stochastic mixed-integer program
Luo Xiaoyu, Gao Chuanhou
We propose to generate Lagrangian cut for two-stage stochastic integer program by batch, in contrast to the existing methods which solve each Lagrangian subproblem at every iterati…
ADPBA: Efficiently generating Lagrangian cuts for two-stage stochastic integer programs
Xiaoyu Luo, Mingming Xu, Chuanhou Gao
The use of Lagrangian cuts proves effective in enhancing the lower bound of the master problem within the execution of benders-type algorithms, particularly in the context of two-s…