Zhang, Yingqian

17 publications

TMLR 2026 End-to-End Deep Reinforcement Learning for Stochastic Multi-Objective Optimization in C-VRPTW Abdo Abouelrous, Laurens Bliek, Yaoxin Wu, Yingqian Zhang

ICLR 2026 Neural Multi-Objective Combinatorial Optimization for Flexible Job Shop Scheduling Problems Igor G. Smit, Yaoxin Wu, Pavel Troubil, Yingqian Zhang, Wim P.M. Nuijten

ICLR 2025 DRoC: Elevating Large Language Models for Complex Vehicle Routing via Decomposed Retrieval of Constraints Xia Jiang, Yaoxin Wu, Chenhao Zhang, Yingqian Zhang

TMLR 2025 Enhancing Remaining Useful Life Prediction with Ensemble Multi-Term Fourier Graph Neural Networks Ya Song, Laurens Bliek, Yaoxin Wu, Yingqian Zhang

ICML 2025 Graph-Supported Dynamic Algorithm Configuration for Multi-Objective Combinatorial Optimization Robbert Reijnen, Yaoxin Wu, Zaharah Bukhsh, Yingqian Zhang

NeurIPS 2025 Large Language Models as End-to-End Combinatorial Optimization Solvers Xia Jiang, Yaoxin Wu, Minshuo Li, Zhiguang Cao, Yingqian Zhang

AAAI 2025 Neural Combinatorial Optimization for Stochastic Flexible Job Shop Scheduling Problems Igor G. Smit, Yaoxin Wu, Pavel Troubil, Yingqian Zhang, Wim P. M. Nuijten

MLJ 2025 Offline Reinforcement Learning for Learning to Dispatch for Job Shop Scheduling Jesse van Remmerden, Zaharah Bukhsh, Yingqian Zhang

IJCAI 2024 Cross-Problem Learning for Solving Vehicle Routing Problems Zhuoyi Lin, Yaoxin Wu, Bangjian Zhou, Zhiguang Cao, Wen Song, Yingqian Zhang, Senthilnath Jayavelu

ACML 2023 Deep Reinforcement Learning for Two-Sided Online Bipartite Matching in Collaborative Order Picking Luca Begnardi, Hendrik Baier, Willem Jaarsveld, Yingqian Zhang

ECML-PKDD 2021 Improving Ambulance Dispatching with Machine Learning and Simulation Nikki Theeuwes, Geert-Jan van Houtum, Yingqian Zhang

ACML 2020 A State Aggregation Approach for Solving Knapsack Problem with Deep Reinforcement Learning Reza Refaei Afshar, Yingqian Zhang, Murat Firat, Uzay Kaymak

ACML 2020 Learning 2-Opt Heuristics for the Traveling Salesman Problem via Deep Reinforcement Learning Paulo R d O Costa, Jason Rhuggenaath, Yingqian Zhang, Alp Akcay

ECML-PKDD 2020 Low-Regret Algorithms for Strategic Buyers with Unknown Valuations in Repeated Posted-Price Auctions Jason Rhuggenaath, Paulo Roberto de Oliveira da Costa, Yingqian Zhang, Alp Akcay, Uzay Kaymak

ECML-PKDD 2019 Data-Driven Policy on Feasibility Determination for the Train Shunting Problem Paulo Roberto de Oliveira da Costa, Jason Rhuggenaath, Yingqian Zhang, Alp Akcay, Wan-Jui Lee, Uzay Kaymak

AAAI 2019 Learning Optimal Classification Trees Using a Binary Linear Program Formulation Sicco Verwer, Yingqian Zhang

JAIR 2014 Finding Optimal Solutions for Voting Game Design Problems Bart de Keijzer, Tomas B. Klos, Yingqian Zhang