A Fast and Efficient Fluid Relaxation Algorithm for Large-Scale Re-entrant Flexible Job Shop Scheduling. - Linshan Ding; Zailin Guan; Zhengmin Zhang (APMS (5), 2021)

Multi-policy deep reinforcement learning for multi-objective multiplicity flexible job shop scheduling. - Linshan Ding; Zailin Guan; Mudassar Rauf; Lei Yue (Swarm Evol. Comput., 2024)

Two-stage double deep Q-network algorithm considering external non-dominant set for multi-objective dynamic flexible job shop scheduling problems. - Lei Yue; Kai Peng; Linshan Ding; Jabir Mumtaz; Libin Lin; Tao Zou (Swarm Evol. Comput., 2024)

An Adaptive Search Algorithm for Multiplicity Dynamic Flexible Job Shop Scheduling with New Order Arrivals. - Linshan Ding; Zailin Guan; Dan Luo; Mudassar Rauf; Weikang Fang (Symmetry, 2024)

Deep reinforcement learning for data-driven scheduling in multi-variety and small-batch flexible job shops: Integrating fluid models for enhanced optimization. - Linshan Ding; Dan Luo; Mudassar Rauf; Lei Yue (Comput. Ind. Eng., 2025)

A novel deep self-learning method for flexible job-shop scheduling problems with multiplicity: Deep reinforcement learning assisted the fluid master-apprentice evolutionary algorithm. - Linshan Ding; Dan Luo; Mudassar Rauf; Lei Yue; Leilei Meng (Swarm Evol. Comput., 2025)