Monitoring Agents using Declarative Planning. - Jürgen Dix; Thomas Eiter; Michael Fink 001; Axel Polleres; Yingqian Zhang 001 (Fundam. Informaticae, 2003)

Distributed Algorithms for Dynamic Survivability of Multiagent Systems. - V. S. Subrahmanian; Sarit Kraus; Yingqian Zhang 001 (CLIMA, 2004)

IMPACT: A Multi-Agent Framework with Declarative Semantics. - Jürgen Dix; Yingqian Zhang 001 (Multi-Agent Programming, 2005)

Towards fault tolerance for multiagent systems. - Yingqian Zhang 001 (AAMAS, 2005)

Distributed task allocation in social networks. - Mathijs de Weerdt; Yingqian Zhang 001; Tomas Klos (AAMAS, 2007)

Plan-Coordination Mechanisms and the Price of Autonomy. - J. Renze Steenhuisen; Cees Witteveen; Yingqian Zhang 001 (CLIMA, 2007)

Preventing Under-Reporting in Social Task Allocation. - Mathijs de Weerdt; Yingqian Zhang 001 (AMEC/TADA, 2008)

Creating incentives to prevent execution failures: an extension of VCG mechanism. - Yingqian Zhang 001; Mathijs de Weerdt (Planning in Multiagent Systems, 2008)

Of Mechanism Design Multiagent Planning. - Roman van der Krogt; Mathijs de Weerdt; Yingqian Zhang 001 (ECAI, 2008)

Autonomous Scheduling. - Chetan Yadati; Cees Witteveen; Yingqian Zhang 001; Mengxiao Wu; Han La Poutré (FCS, 2008)

Autonomous Scheduling with Unbounded and Bounded Agents. - Chetan Yadati; Cees Witteveen; Yingqian Zhang 001; Mengxiao Wu; Han La Poutré (MATES, 2008)

On the Complexity of Efficiency and Envy-Freeness in Fair Division of Indivisible Goods with Additive Preferences. - Bart de Keijzer; Sylvain Bouveret; Tomas Klos; Yingqian Zhang 001 (ADT, 2009)

Creating Incentives to Prevent Intentional Execution Failures. - Yingqian Zhang 001; Mathijs de Weerdt (IAT, 2009)

Computing the fault tolerance of multi-agent deployment. - Yingqian Zhang 001; Efrat Manisterski; Sarit Kraus; V. S. Subrahmanian; David Peleg (Artif. Intell., 2009)

Enumeration and exact design of weighted voting games. - Bart de Keijzer; Tomas Klos; Yingqian Zhang 001 (AAMAS, 2010)

Coordinating Agents - An Analysis of Coordination in Supply-chain Management Tasks. - Chetan Yadati; Cees Witteveen; Yingqian Zhang 001 (ICAART (2), 2010)

Coordination by design and the price of autonomy. - Adriaan ter Mors; Chetan Yadati; Cees Witteveen; Yingqian Zhang 001 (Auton. Agents Multi Agent Syst., 2010)

Revenue prediction in budget-constrained sequential auctions with complementarities. - Sicco Verwer; Yingqian Zhang 001 (AAMAS, 2012)

Mechanism for Robust Procurements. - Yingqian Zhang 001; Sicco Verwer (PRIMA, 2012)

Multiagent task allocation in social networks. - Mathijs de Weerdt; Yingqian Zhang 001; Tomas Klos (Auton. Agents Multi Agent Syst., 2012)

Solving Weighted Voting Game Design Problems Optimally: Representations, Synthesis, and Enumeration - Bart de Keijzer; Tomas B. Klos; Yingqian Zhang 001 (CoRR, 2012)

A Tabu Search Algorithm for application placement in computer clustering. - Jelmer P. van der Gaast; Cornelius A. Rietveld; Adriana F. Gabor; Yingqian Zhang 001 (Comput. Oper. Res., 2014)

Learning optimization models in the presence of unknown relations. - Sicco Verwer; Yingqian Zhang 001; Qing Chuan Ye (CoRR, 2014)

Finding Optimal Solutions for Voting Game Design Problems. - Bart de Keijzer; Tomas B. Klos; Yingqian Zhang 001 (J. Artif. Intell. Res., 2014)

Fair task allocation in transportation. - Qing Chuan Ye; Yingqian Zhang 001; Rommert Dekker (CoRR, 2015)

Participation Behavior and Social Welfare in Repeated Task Allocations. - Qing Chuan Ye; Yingqian Zhang 001 (ICA, 2016)

Schedule-based execution bottleneck identification in a job shop. - Junqiang Wang; Jian Chen 022; Yingqian Zhang 001; George Q. Huang (Comput. Ind. Eng., 2016)

Learning Decision Trees with Flexible Constraints and Objectives Using Integer Optimization. - Sicco Verwer; Yingqian Zhang 001 (CPAIOR, 2017)

Modeling participation behavior in repeated task allocations with fuzzy connectives. - Qing Chuan Ye; Yingqian Zhang 001; Uzay Kaymak (SMC, 2017)

Auction optimization using regression trees and linear models as integer programs. - Sicco Verwer; Yingqian Zhang 001; Qing Chuan Ye (Artif. Intell., 2017)

Two-agent scheduling on a single parallel-batching machine with equal processing time and non-identical job sizes. - Jun-Qiang Wang; Guo-Qiang Fan; Yingqian Zhang 001; Cheng-Wu Zhang; Joseph Y.-T. Leung (Eur. J. Oper. Res., 2017)

Learning fuzzy decision trees using integer programming. - Jason Rhuggenaath; Yingqian Zhang 001; Alp Akcay; Uzay Kaymak; Sicco Verwer (FUZZ-IEEE, 2018)

Shunting Trains with Deep Reinforcement Learning. - Evertjan Peer; Vlado Menkovski; Yingqian Zhang 001; Wan-Jui Lee (SMC, 2018)

Constructing classification trees using column generation. - Murat Firat; Guillaume Crognier; Adriana F. Gabor; Yingqian Zhang 001; Cor A. J. Hurkens (CoRR, 2018)

Learning Optimal Classification Trees Using a Binary Linear Program Formulation. - Sicco Verwer; Yingqian Zhang 001 (AAAI, 2019)

Formalization and Improvement of Ambulance Dispatching in Brabant-Zuidoost. - Nikki Theeuwes; Geert-Jan van Houtum; Yingqian Zhang 001; Björn Gadet (BNAIC/BENELEARN, 2019)

A PSO-based Algorithm for Reserve Price Optimization in Online Ad Auctions. - Jason Rhuggenaath; Alp Akcay; Yingqian Zhang 001; Uzay Kaymak (CEC, 2019)

A Decision Support Method to Increase the Revenue of Ad Publishers in Waterfall Strategy. - Reza Refaei Afshar; Yingqian Zhang 001; Murat Firat; Uzay Kaymak (CIFEr, 2019)

Optimizing reserve prices for publishers in online ad auctions. - Jason Rhuggenaath; Alp Akcay; Yingqian Zhang 001; Uzay Kaymak (CIFEr, 2019)

Fuzzy Logic based Pricing combined with Adaptive Search for Reserve Price Optimization in Online Ad Auctions. - Jason Rhuggenaath; Alp Akcay; Yingqian Zhang 001; Uzay Kaymak (FUZZ-IEEE, 2019)

A Reinforcement Learning Method to Select Ad Networks in Waterfall Strategy. - Reza Refaei Afshar; Yingqian Zhang 001; Murat Firat; Uzay Kaymak (ICAART (2), 2019)

Reinforcement Learning Method for Ad Networks Ordering in Real-Time Bidding. - Reza Refaei Afshar; Yingqian Zhang 001; Murat Firat; Uzay Kaymak (ICAART (Revised Selected Papers), 2019)

Boosting Local Search Using Machine Learning: A Study on Improving Local Search by Graph Classification in Determining Capacity of Shunting Yards. - Arno van de Ven; Yingqian Zhang 001; Wan-Jui Lee (ICAART (Revised Selected Papers), 2019)

Determining Capacity of Shunting Yards by Combining Graph Classification with Local Search. - Arno van de Ven; Yingqian Zhang 001; Wan-Jui Lee; Rik Eshuis; Anna Wilbik (ICAART (2), 2019)

Data-Driven Policy on Feasibility Determination for the Train Shunting Problem. - Paulo Roberto de Oliveira da Costa; Jason Rhuggenaath; Yingqian Zhang 001; Alp Akcay; Wan-Jui Lee; Uzay Kaymak (ECML/PKDD (3), 2019)

Term Based Semantic Clusters for Very Short Text Classification. - Jasper Paalman; Shantanu Mullick; Kalliopi Zervanou; Yingqian Zhang 001 (RANLP, 2019)

A heuristic policy for dynamic pricing and demand learning with limited price changes and censored demand. - Jason Rhuggenaath; Paulo Roberto de Oliveira da Costa; Alp Akcay; Yingqian Zhang 001; Uzay Kaymak (SMC, 2019)

Machine Learning based Simulation Optimisation for Trailer Management. - Dylan Rijnen; Jason Rhuggenaath; Paulo Roberto de Oliveira da Costa; Yingqian Zhang 001 (SMC, 2019)

Optimal display-ad allocation with guaranteed contracts and supply side platforms. - Jason Rhuggenaath; Alp Akcay; Yingqian Zhang 001; Uzay Kaymak (Comput. Ind. Eng., 2019)

Solving bin-packing problems under privacy preservation: Possibilities and trade-offs. - Rowan Hoogervorst; Yingqian Zhang 001; Gamze Tillem; Zekeriya Erkin; Sicco Verwer (Inf. Sci., 2019)

A State Aggregation Approach for Solving Knapsack Problem with Deep Reinforcement Learning. - Reza Refaei Afshar; Yingqian Zhang 001; Murat Firat; Uzay Kaymak (ACML, 2020)

Learning 2-opt Heuristics for the Traveling Salesman Problem via Deep Reinforcement Learning. - Paulo R. de O. da Costa; Jason Rhuggenaath; Yingqian Zhang 001; Alp Akcay (ACML, 2020)

Lost and Found: Predicting Airline Baggage At-risk of Being Mishandled. - Herbert van Leeuwen; Yingqian Zhang 001; Kalliopi Zervanou; Shantanu Mullick; Uzay Kaymak; Tom de Ruijter (ICAART (2), 2020)

Dynamic Pricing Using Thompson Sampling with Fuzzy Events. - Jason Rhuggenaath; Paulo Roberto de Oliveira da Costa; Yingqian Zhang 001; Alp Akcay; Uzay Kaymak (IPMU (1), 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 001; Alp Akcay; Uzay Kaymak (ECML/PKDD (2), 2020)

Reserve price optimization with header bidding and Ad Exchange. - Reza Refaei Afshar; Yingqian Zhang 001; Murat Firat; Uzay Kaymak; Ali Izzet Metin; Gönenç Seçil Tarakçioglu; Cosku Bas (SMC, 2020)

Predicting Water Pipe Failures with a Recurrent Neural Hawkes Process Model. - Jeroen Verheugd; Paulo Roberto de Oliveira da Costa; Reza Refaei Afshar; Yingqian Zhang 001; Sjoerd Boersma (SMC, 2020)

Combining Deep Reinforcement Learning with Search Heuristics for Solving Multi-Agent Path Finding in Segment-based Layouts. - Robbert Reijnen; Yingqian Zhang 001; Wim Nuijten; Çaglar Senaras; Mariana Goldak-Altgassen (SSCI, 2020)

Column generation based heuristic for learning classification trees. - Murat Firat; Guillaume Crognier; Adriana F. Gabor; Cor A. J. Hurkens; Yingqian Zhang 001 (Comput. Oper. Res., 2020)

Algorithms for slate bandits with non-separable reward functions. - Jason Rhuggenaath; Alp Akcay; Yingqian Zhang 001; Uzay Kaymak (CoRR, 2020)

Solving the Order Batching and Sequencing Problem using Deep Reinforcement Learning. - Bram Cals; Yingqian Zhang 001; Remco M. Dijkman; Claudy van Dorst (CoRR, 2020)

Regular Expression Learning from Positive Examples Based on Integer Programming. - Juntao Gao; Yingqian Zhang 001 (Int. J. Softw. Eng. Knowl. Eng., 2020)

Remaining useful lifetime prediction via deep domain adaptation. - Paulo Roberto de Oliveira da Costa; Alp Akcay; Yingqian Zhang 001; Uzay Kaymak (Reliab. Eng. Syst. Saf., 2020)

A Reward Shaping Approach for Reserve Price Optimization using Deep Reinforcement Learning. - Reza Refaei Afshar; Jason Rhuggenaath; Yingqian Zhang 001; Uzay Kaymak (IJCNN, 2021)

Learning 2-opt Local Search from Heuristics as Expert Demonstrations. - Paulo da Costa 001; Yingqian Zhang 001; Alp Akcay; Uzay Kaymak (IJCNN, 2021)

The EURO Meets NeurIPS 2022 Vehicle Routing Competition. - Wouter Kool 001; Laurens Bliek; Danilo Numeroso; Yingqian Zhang 001; Tom Catshoek; Kevin Tierney; Thibaut Vidal; Joaquim A. S. Gromicho (NeurIPS (Competition and Demos), 2021)

Improving Ambulance Dispatching with Machine Learning and Simulation. - Nikki Theeuwes; Geert-Jan van Houtum; Yingqian Zhang 001 (ECML/PKDD (4), 2021)

Relation Representation Learning for Special Cargo Ontology. - Vahideh Reshadat; Alp Akcay; Kalliopi Zervanou; Yingqian Zhang 001; Eelco de Jong (SSCI, 2021)

Data driven design for online industrial auctions. - Qing Chuan Ye; Jason Rhuggenaath; Yingqian Zhang 001; Sicco Verwer; Michiel Jurgen Hilgeman (Ann. Math. Artif. Intell., 2021)

Preface. - Yingqian Zhang 001; Michele Lombardi 001; Patrick De Causmaecker (Ann. Math. Artif. Intell., 2021)

Solving the online batching problem using deep reinforcement learning. - Bram Cals; Yingqian Zhang 001; Remco M. Dijkman; Claudy van Dorst (Comput. Ind. Eng., 2021)

Maximizing revenue for publishers using header bidding and ad exchange auctions. - Jason Rhuggenaath; Reza Refaei Afshar; Alp Akcay; Yingqian Zhang 001; Uzay Kaymak; Fatih Çolak; Muratcan Tanyerli (Oper. Res. Lett., 2021)

Learning 2-Opt Heuristics for Routing Problems via Deep Reinforcement Learning. - Paulo da Costa 001; Jason Rhuggenaath; Yingqian Zhang 001; Alp Akcay; Uzay Kaymak (SN Comput. Sci., 2021)

Knowledge Modeling and Incident Analysis for Special Cargo. - Vahideh Reshadat; Tess Kolkman; Kalliopi Zervanou; Yingqian Zhang 001; Alp Akçay; Carlijn Snijder; Ryan McDonnell; Karel Schorer; Casper Wichers; Thomas Koch 005; Elenna R. Dugundji; Eelco de Jong (Technologies and Applications for Big Data Value, 2022)

Deep Reinforcement Learning for a Multi-Objective Online Order Batching Problem. - Martijn Beeks; Reza Refaei Afshar; Yingqian Zhang 001; Remco M. Dijkman; Claudy van Dorst; Stijn de Looijer (ICAPS, 2022)

Comparing Interpretable AI Approaches for the Clinical Environment: an Application to COVID-19. - Mohsen Abbaspour Onari; Marco S. Nobile; Isel Grau; Caro Fuchs; Yingqian Zhang 001; Arjen-Kars Boer; Volkher Scharnhorst (CIBCB, 2022)

Grouping of Maintenance Actions with Deep Reinforcement Learning and Graph Convolutional Networks. - David Kerkkamp; Zaharah Allah Bukhsh; Yingqian Zhang 001; Nils Jansen 001 (ICAART (2), 2022)

Deep Reinforcement Learning for Adaptive Parameter Control in Differential Evolution for Multi-Objective Optimization. - Robbert Reijnen; Yingqian Zhang 001; Zaharah Allah Bukhsh; Mateusz Guzek (SSCI, 2022)

Optimizing the inventory and fulfillment of an omnichannel retailer: a stochastic approach with scenario clustering. - Abdo Abouelrous; Adriana F. Gabor; Yingqian Zhang 001 (Comput. Ind. Eng., 2022)

Automated Reinforcement Learning: An Overview. - Reza Refaei Afshar; Yingqian Zhang 001; Joaquin Vanschoren; Uzay Kaymak (CoRR, 2022)

The First AI4TSP Competition: Learning to Solve Stochastic Routing Problems. - Laurens Bliek; Paulo da Costa 001; Reza Refaei Afshar; Yingqian Zhang 001; Tom Catshoek; Daniël Vos; Sicco Verwer; Fynn Schmitt-Ulms; André Hottung; Tapan Shah 001; Meinolf Sellmann; Kevin Tierney; et al. (CoRR, 2022)

Operator Selection in Adaptive Large Neighborhood Search using Deep Reinforcement Learning. - Robbert Reijnen; Yingqian Zhang 001; Hoong Chuin Lau; Zaharah Allah Bukhsh (CoRR, 2022)

Learning Adaptive Evolutionary Computation for Solving Multi-Objective Optimization Problems. - Remco Coppens; Robbert Reijnen; Yingqian Zhang 001; Laurens Bliek; Berend Steenhuisen (CoRR, 2022)

Dynamic Ad Network Ordering Method Using Reinforcement Learning. - Reza Refaei Afshar; Yingqian Zhang 001; Uzay Kaymak (Int. J. Comput. Intell. Syst., 2022)

Setting Reserve Prices in Second-Price Auctions with Unobserved Bids. - Jason Rhuggenaath; Alp Akcay; Yingqian Zhang 001; Uzay Kaymak (INFORMS J. Comput., 2022)

Deep Reinforcement Learning for Two-sided Online Bipartite Matching in Collaborative Order Picking. - Luca Begnardi; Hendrik Baier; Willem van Jaarsveld; Yingqian Zhang 001 (ACML, 2023)

Trustworthy Artificial Intelligence in Medical Applications: A Mini Survey. - Mohsen Abbaspour Onari; Isel Grau; Marco S. Nobile; Yingqian Zhang 001 (CIBCB, 2023)

Learning to Adapt Genetic Algorithms for Multi-Objective Flexible Job Shop Scheduling Problems. - Robbert Reijnen; Yingqian Zhang 001; Zaharah Allah Bukhsh; Mateusz Guzek (GECCO Companion, 2023)

Discovering Explicit Scale-Up Criteria in Crisis Response with Decision Mining. - Britt Lukassen; Laura Genga; Yingqian Zhang 001 (LION, 2023)

Auction-based network slicing for 5G RAN. - Ligia Maria Moreira Zorello; Kazem Eradatmand; Sebastian Troia; Achille Pattavina; Yingqian Zhang 001; Guido Maier (NetSoft, 2023)

Digital Twin Applications in Urban Logistics: An Overview. - Abdo Abouelrous; Laurens Bliek; Yingqian Zhang 001 (CoRR, 2023)

Measuring Perceived Trust in XAI-Assisted Decision-Making by Eliciting a Mental Model. - Mohsen Abbaspour Onari; Isel Grau; Marco S. Nobile; Yingqian Zhang 001 (CoRR, 2023)

Job Shop Scheduling Benchmark: Environments and Instances for Learning and Non-learning Methods. - Robbert Reijnen; Kjell van Straaten; Zaharah Allah Bukhsh; Yingqian Zhang 001 (CoRR, 2023)

Parcel loss prediction in last-mile delivery: deep and non-deep approaches with insights from Explainable AI. - Jan de Leeuw; Zaharah Allah Bukhsh; Yingqian Zhang 001 (CoRR, 2023)

Policies for the dynamic traveling maintainer problem with alerts. - Paulo da Costa 001; Peter Verleijsdonk; Simon Voorberg; Alp Akcay; Stella Kapodistria; Willem van Jaarsveld; Yingqian Zhang 001 (Eur. J. Oper. Res., 2023)

The first AI4TSP competition: Learning to solve stochastic routing problems. - Yingqian Zhang 001; Laurens Bliek; Paulo da Costa 001; Reza Refaei Afshar; Robbert Reijnen; Tom Catshoek; Daniël Vos; Sicco Verwer; Fynn Schmitt-Ulms; André Hottung; Tapan Shah 001; Meinolf Sellmann; et al. (Artif. Intell., 2023)

An Automated Deep Reinforcement Learning Pipeline for Dynamic Pricing. - Reza Refaei Afshar; Jason Rhuggenaath; Yingqian Zhang 001; Uzay Kaymak (IEEE Trans. Artif. Intell., 2023)

SCRE: special cargo relation extraction using representation learning. - Vahideh Reshadat; Alp Akcay; Kalliopi Zervanou; Yingqian Zhang 001; Eelco de Jong (Neural Comput. Appl., 2023)

Online Control of Adaptive Large Neighborhood Search Using Deep Reinforcement Learning. - Robbert Reijnen; Yingqian Zhang 001; Hoong Chuin Lau; Zaharah Allah Bukhsh (ICAPS, 2024)

Cross-Problem Learning for Solving Vehicle Routing Problems. - Zhuoyi Lin; Yaoxin Wu; Bangjian Zhou; Zhiguang Cao; Wen Song; Yingqian Zhang 001; Senthilnath Jayavelu (IJCAI, 2024)

Learning Efficient and Fair Policies for Uncertainty-Aware Collaborative Human-Robot Order Picking. - Igor G. Smit; Zaharah Allah Bukhsh; Mykola Pechenizkiy; Kostas Alogariastos; Kasper Hendriks; Yingqian Zhang 001 (CoRR, 2024)

Deep Multi-Objective Reinforcement Learning for Utility-Based Infrastructural Maintenance Optimization. - Jesse van Remmerden; Maurice Kenter; Diederik M. Roijers; Charalampos Andriotis; Yingqian Zhang 001; Zaharah Bukhsh (CoRR, 2024)

UNCO: Towards Unifying Neural Combinatorial Optimization through Large Language Model. - Xia Jiang; Yaoxin Wu; Yuan Wang; Yingqian Zhang 001 (CoRR, 2024)

Real-Time Data-Driven Maintenance Logistics: A Public-Private Collaboration. - Willem van Jaarsveld; Alp Akçay; Laurens Bliek; Paulo da Costa 001; Mathijs de Weerdt; Rik Eshuis; Stella Kapodistria; Uzay Kaymak; Verus Pronk; Geert-Jan van Houtum; Peter Verleijsdonk; Sicco Verwer; et al. (Commit2Data, 2024)

Neural Combinatorial Optimization for Stochastic Flexible Job Shop Scheduling Problems. - Igor G. Smit; Yaoxin Wu; Pavel Troubil; Yingqian Zhang 001; Wim P. M. Nuijten (AAAI, 2025)

Algorithm Configuration in Sequential Decision-Making. - Luca Begnardi; Bart von Meijenfeldt; Yingqian Zhang 001; Willem van Jaarsveld; Hendrik Baier (CPAIOR (1), 2025)

Revisit the Algorithm Selection Problem for TSP with Spatial Information Enhanced Graph Neural Networks. - Ya Song; Laurens Bliek; Yingqian Zhang 001 (ICAART (3), 2025)

DRoC: Elevating Large Language Models for Complex Vehicle Routing via Decomposed Retrieval of Constraints. - Xia Jiang; Yaoxin Wu; Chenhao Zhang; Yingqian Zhang 001 (ICLR, 2025)

Graph neural networks for job shop scheduling problems: A survey. - Igor G. Smit; Jianan Zhou 002; Robbert Reijnen; Yaoxin Wu; Jian Chen 022; Cong Zhang; Zaharah Bukhsh; Yingqian Zhang 001; Wim Nuijten (Comput. Oper. Res., 2025)

Solving two-stage stochastic integer programs via representation learning. - Yaoxin Wu; Zhiguang Cao; Wen Song; Yingqian Zhang 001 (Neural Networks, 2025)

Enhancing Remaining Useful Life Prediction with Ensemble Multi-Term Fourier Graph Neural Networks. - Ya Song; Laurens Bliek; Yaoxin Wu; Yingqian Zhang 001 (Trans. Mach. Learn. Res., 2025)

Reinforcement Learning for Solving the Pricing Problem in Column Generation: Applications to Vehicle Routing. - Abdo Abouelrous; Laurens Bliek; Adriana F. Gabor; Yaoxin Wu; Yingqian Zhang 001 (CoRR, 2025)

Graph Reduction with Unsupervised Learning in Column Generation: A Routing Application. - Abdo Abouelrous; Laurens Bliek; Adriana F. Gabor; Yaoxin Wu; Yingqian Zhang 001 (CoRR, 2025)

Graph-Supported Dynamic Algorithm Configuration for Multi-Objective Combinatorial Optimization. - Robbert Reijnen; Yaoxin Wu; Zaharah Bukhsh; Yingqian Zhang 001 (CoRR, 2025)

Offline reinforcement learning for learning to dispatch for job shop scheduling. - Jesse van Remmerden; Zaharah Bukhsh; Yingqian Zhang 001 (Mach. Learn., 2025)