An Iterated Hybrid Local Search Algorithm for Pick-and-Place Sequence Optimization. - Jinsheng Gao; Xiaomin Zhu; Anbang Liu; Qingyang Meng; Runtong Zhang (Symmetry, 2018)

EDA based Deep Neural Network Parameter Optimization. - Qingyang Xu; Anbang Liu (CSAE, 2019)

Random mask-based estimation of the distribution algorithm for stacked auto-encoder one-step pre-training. - Qingyang Xu; Anbang Liu; Xianfeng Yuan; Yong Song; Chengjin Zhang; Yibin Li 001 (Comput. Ind. Eng., 2021)

A Novel Integer Linear Programming Formulation for Job-Shop Scheduling Problems. - Anbang Liu; Peter B. Luh; Bing Yan; Mikhail A. Bragin (IEEE Robotics Autom. Lett., 2021)

Integrating Machine Learning and Mathematical Optimization for Job Shop Scheduling. - Anbang Liu (IEEE DataPort, 2022)

A Mixed Integer Linear Programming Formulation for Subway Timetable Optimization Problems with Passenger Waiting and Energy Saving Objectives. - Anbang Liu; Xi Chen (CASE, 2023)

Integrating Machine Learning and Mathematical Optimization for Job Shop Scheduling. - Anbang Liu; Peter B. Luh; Kailai Sun; Mikhail A. Bragin; Bing Yan (IEEE Trans Autom. Sci. Eng., 2024)

Unsupervised Motion-Robust Self-Distillation Framework for Remote Physiological Measurement. - Anbang Liu; Shanlin Xiao; Wenming Zheng (ICASSP, 2025)

Integrated Offline and Online Learning to Solve a Large Class of Scheduling Problems. - Anbang Liu; Zhi-Long Chen; Jinyang Jiang 001; Xi Chen (CoRR, 2025)

Accelerating Level-Value Adjustment for the Polyak Stepsize. - Anbang Liu; Mikhail A. Bragin; Xi Chen 036; Xiaohong Guan (J. Optim. Theory Appl., 2025)