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ORCIDYingqian Zhang 0001
Person information
- affiliation: Eindhoven University of Technology, The Netherlands
- affiliation: Erasmus University Rotterdam, The Netherlands
- affiliation: Delft University of Technology, The Netherlands
- affiliation (PhD): University of Manchester, School of Computer Science, UK
Other persons with the same name
- Yingqian Zhang 0002
![[0000-0001-9568-0392]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0001-9568-0392")
(aka: Ying-Qian Zhang 0002) — Xiamen University Malaysia (XMUM), Sepang, Malaysia (and 2 more) - Yingqian Zhang 0003 — PLA General Hospital, Beijing, China
- Yingqian Zhang 0004 — Sichuan University of Science and Engineering, Zigong, China
- Yingqian Zhang 0005 — Zhejiang University, Department of Control Science and Engineering, Hangzhou, China
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2020 – today
- 2024
[c62]Robbert Reijnen, Yingqian Zhang, Hoong Chuin Lau, Zaharah Allah Bukhsh:
Online Control of Adaptive Large Neighborhood Search Using Deep Reinforcement Learning. ICAPS 2024: 475-483- [c61]Zhuoyi Lin, Yaoxin Wu, Bangjian Zhou, Zhiguang Cao, Wen Song, Yingqian Zhang, Senthilnath Jayavelu:
Cross-Problem Learning for Solving Vehicle Routing Problems. IJCAI 2024: 6958-6966 - [p3]Willem van Jaarsveld, Alp Akçay, Laurens Bliek, Paulo da Costa, Mathijs de Weerdt, Rik Eshuis, Stella Kapodistria, Uzay Kaymak, Verus Pronk, Geert-Jan van Houtum, Peter Verleijsdonk, Sicco Verwer, Simon Voorberg, Yingqian Zhang:
Real-Time Data-Driven Maintenance Logistics: A Public-Private Collaboration. Commit2Data 2024: 5:1-5:13 - [i28]Igor G. Smit, Zaharah Allah Bukhsh, Mykola Pechenizkiy, Kostas Alogariastos, Kasper Hendriks, Yingqian Zhang:
Learning Efficient and Fair Policies for Uncertainty-Aware Collaborative Human-Robot Order Picking. CoRR abs/2404.08006 (2024) - [i27]Zhuoyi Lin, Yaoxin Wu, Bangjian Zhou, Zhiguang Cao, Wen Song, Yingqian Zhang, Senthilnath Jayavelu:
Cross-Problem Learning for Solving Vehicle Routing Problems. CoRR abs/2404.11677 (2024) - [i26]Jesse van Remmerden, Maurice Kenter, Diederik M. Roijers, Charalampos Andriotis, Yingqian Zhang, Zaharah Bukhsh:
Deep Multi-Objective Reinforcement Learning for Utility-Based Infrastructural Maintenance Optimization. CoRR abs/2406.06184 (2024) - [i25]Igor G. Smit, Jianan Zhou, Robbert Reijnen, Yaoxin Wu, Jian Chen, Cong Zhang, Zaharah Bukhsh, Wim Nuijten, Yingqian Zhang:
Graph Neural Networks for Job Shop Scheduling Problems: A Survey. CoRR abs/2406.14096 (2024) - [i24]Xia Jiang, Yaoxin Wu, Yuan Wang, Yingqian Zhang:
UNCO: Towards Unifying Neural Combinatorial Optimization through Large Language Model. CoRR abs/2408.12214 (2024) - [i23]Jesse van Remmerden, Zaharah Bukhsh, Yingqian Zhang:
Offline Reinforcement Learning for Learning to Dispatch for Job Shop Scheduling. CoRR abs/2409.10589 (2024) - 2023
- [j26]Yingqian Zhang, Laurens Bliek, Paulo da Costa, Reza Refaei Afshar, Robbert Reijnen, Tom Catshoek, Daniël Vos, Sicco Verwer, Fynn Schmitt-Ulms, André Hottung, Tapan Shah, Meinolf Sellmann, Kevin Tierney, Carl Perreault-Lafleur, Caroline Leboeuf, Federico Bobbio, Justine Pepin, Warley Almeida Silva, Ricardo Gama, Hugo L. Fernandes, Martin Zaefferer, Manuel López-Ibáñez, Ekhine Irurozki:
The first AI4TSP competition: Learning to solve stochastic routing problems. Artif. Intell. 319: 103918 (2023) - [j25]Paulo da Costa, Peter Verleijsdonk, Simon Voorberg, Alp Akcay, Stella Kapodistria, Willem van Jaarsveld, Yingqian Zhang:
Policies for the dynamic traveling maintainer problem with alerts. Eur. J. Oper. Res. 305(3): 1141-1152 (2023) - [j24]Vahideh Reshadat, Alp Akcay, Kalliopi Zervanou, Yingqian Zhang, Eelco de Jong:
SCRE: special cargo relation extraction using representation learning. Neural Comput. Appl. 35(25): 18783-18801 (2023) - [j23]Reza Refaei Afshar, Jason Rhuggenaath, Yingqian Zhang, Uzay Kaymak:
An Automated Deep Reinforcement Learning Pipeline for Dynamic Pricing. IEEE Trans. Artif. Intell. 4(3): 428-437 (2023) - [c60]Luca Begnardi, Hendrik Baier, Willem van Jaarsveld, Yingqian Zhang:
Deep Reinforcement Learning for Two-sided Online Bipartite Matching in Collaborative Order Picking. ACML 2023: 121-136 - [c59]Mohsen Abbaspour Onari, Isel Grau, Marco S. Nobile, Yingqian Zhang:
Trustworthy Artificial Intelligence in Medical Applications: A Mini Survey. CIBCB 2023: 1-8 - [c58]Robbert Reijnen, Yingqian Zhang, Zaharah Allah Bukhsh, Mateusz Guzek:
Learning to Adapt Genetic Algorithms for Multi-Objective Flexible Job Shop Scheduling Problems. GECCO Companion 2023: 315-318 - [c57]Britt Lukassen, Laura Genga, Yingqian Zhang:
Discovering Explicit Scale-Up Criteria in Crisis Response with Decision Mining. LION 2023: 459-474 - [c56]Ligia Maria Moreira Zorello, Kazem Eradatmand, Sebastian Troia, Achille Pattavina, Yingqian Zhang, Guido Maier:
Auction-based network slicing for 5G RAN. NetSoft 2023: 390-395 - [i22]Abdo Abouelrous, Laurens Bliek, Yingqian Zhang:
Digital Twin Applications in Urban Logistics: An Overview. CoRR abs/2302.00484 (2023) - [i21]Ya Song, Laurens Bliek, Yingqian Zhang:
Revisit the Algorithm Selection Problem for TSP with Spatial Information Enhanced Graph Neural Networks. CoRR abs/2302.04035 (2023) - [i20]Mohsen Abbaspour Onari, Isel Grau, Marco S. Nobile, Yingqian Zhang:
Measuring Perceived Trust in XAI-Assisted Decision-Making by Eliciting a Mental Model. CoRR abs/2307.11765 (2023) - [i19]Robbert Reijnen, Kjell van Straaten, Zaharah Allah Bukhsh, Yingqian Zhang:
Job Shop Scheduling Benchmark: Environments and Instances for Learning and Non-learning Methods. CoRR abs/2308.12794 (2023) - [i18]Jan de Leeuw, Zaharah Allah Bukhsh, Yingqian Zhang:
Parcel loss prediction in last-mile delivery: deep and non-deep approaches with insights from Explainable AI. CoRR abs/2310.16602 (2023) - 2022
- [j22]Abdo Abouelrous, Adriana F. Gabor, Yingqian Zhang:
Optimizing the inventory and fulfillment of an omnichannel retailer: a stochastic approach with scenario clustering. Comput. Ind. Eng. 173: 108723 (2022) - [j21]Reza Refaei Afshar, Yingqian Zhang, Uzay Kaymak:
Dynamic Ad Network Ordering Method Using Reinforcement Learning. Int. J. Comput. Intell. Syst. 15(1): 27 (2022) - [j20]Jason Rhuggenaath, Alp Akcay, Yingqian Zhang, Uzay Kaymak:
Setting Reserve Prices in Second-Price Auctions with Unobserved Bids. INFORMS J. Comput. 34(6): 2950-2967 (2022) - [c55]Martijn Beeks, Reza Refaei Afshar, Yingqian Zhang, Remco M. Dijkman, Claudy van Dorst, Stijn de Looijer:
Deep Reinforcement Learning for a Multi-Objective Online Order Batching Problem. ICAPS 2022: 435-443 - [c54]Mohsen Abbaspour Onari, Marco S. Nobile, Isel Grau, Caro Fuchs, Yingqian Zhang, Arjen-Kars Boer, Volkher Scharnhorst:
Comparing Interpretable AI Approaches for the Clinical Environment: an Application to COVID-19. CIBCB 2022: 1-8 - [c53]David Kerkkamp, Zaharah Allah Bukhsh, Yingqian Zhang, Nils Jansen:
Grouping of Maintenance Actions with Deep Reinforcement Learning and Graph Convolutional Networks. ICAART (2) 2022: 574-585 - [c52]Robbert Reijnen, Yingqian Zhang, Zaharah Allah Bukhsh, Mateusz Guzek:
Deep Reinforcement Learning for Adaptive Parameter Control in Differential Evolution for Multi-Objective Optimization. SSCI 2022: 804-811 - [p2]Vahideh Reshadat, Tess Kolkman, Kalliopi Zervanou, Yingqian Zhang, Alp Akçay, Carlijn Snijder, Ryan McDonnell, Karel Schorer, Casper Wichers, Thomas Koch, Elenna R. Dugundji, Eelco de Jong:
Knowledge Modeling and Incident Analysis for Special Cargo. Technologies and Applications for Big Data Value 2022: 519-544 - [i17]Reza Refaei Afshar, Yingqian Zhang, Joaquin Vanschoren, Uzay Kaymak:
Automated Reinforcement Learning: An Overview. CoRR abs/2201.05000 (2022) - [i16]Laurens Bliek, Paulo da Costa, Reza Refaei Afshar, Yingqian Zhang, Tom Catshoek, Daniël Vos, Sicco Verwer, Fynn Schmitt-Ulms, André Hottung, Tapan Shah, Meinolf Sellmann, Kevin Tierney, Carl Perreault-Lafleur, Caroline Leboeuf, Federico Bobbio, Justine Pepin, Warley Almeida Silva, Ricardo Gama, Hugo L. Fernandes, Martin Zaefferer, Manuel López-Ibáñez, Ekhine Irurozki:
The First AI4TSP Competition: Learning to Solve Stochastic Routing Problems. CoRR abs/2201.10453 (2022) - [i15]Robbert Reijnen, Yingqian Zhang, Hoong Chuin Lau, Zaharah Allah Bukhsh:
Operator Selection in Adaptive Large Neighborhood Search using Deep Reinforcement Learning. CoRR abs/2211.00759 (2022) - [i14]Remco Coppens, Robbert Reijnen, Yingqian Zhang, Laurens Bliek, Berend Steenhuisen:
Learning Adaptive Evolutionary Computation for Solving Multi-Objective Optimization Problems. CoRR abs/2211.09719 (2022) - 2021
- [j19]Yingqian Zhang, Michele Lombardi, Patrick De Causmaecker:
Preface. Ann. Math. Artif. Intell. 89(7): 615-616 (2021) - [j18]Qing Chuan Ye, Jason Rhuggenaath, Yingqian Zhang, Sicco Verwer, Michiel Jurgen Hilgeman:
Data driven design for online industrial auctions. Ann. Math. Artif. Intell. 89(7): 675-691 (2021) - [j17]Bram Cals, Yingqian Zhang, Remco M. Dijkman, Claudy van Dorst:
Solving the online batching problem using deep reinforcement learning. Comput. Ind. Eng. 156: 107221 (2021) - [j16]Jason Rhuggenaath, Reza Refaei Afshar, Alp Akcay, Yingqian Zhang, Uzay Kaymak, Fatih Çolak, Muratcan Tanyerli:
Maximizing revenue for publishers using header bidding and ad exchange auctions. Oper. Res. Lett. 49(2): 250-256 (2021) - [j15]Paulo da Costa, Jason Rhuggenaath, Yingqian Zhang, Alp Akcay, Uzay Kaymak:
Learning 2-Opt Heuristics for Routing Problems via Deep Reinforcement Learning. SN Comput. Sci. 2(5): 388 (2021) - [c51]Reza Refaei Afshar, Jason Rhuggenaath, Yingqian Zhang, Uzay Kaymak:
A Reward Shaping Approach for Reserve Price Optimization using Deep Reinforcement Learning. IJCNN 2021: 1-8 - [c50]Paulo da Costa, Yingqian Zhang, Alp Akcay, Uzay Kaymak:
Learning 2-opt Local Search from Heuristics as Expert Demonstrations. IJCNN 2021: 1-8 - [c49]Wouter Kool, Laurens Bliek, Danilo Numeroso, Yingqian Zhang, Tom Catshoek, Kevin Tierney, Thibaut Vidal, Joaquim A. S. Gromicho:
The EURO Meets NeurIPS 2022 Vehicle Routing Competition. NeurIPS (Competition and Demos) 2021: 35-49 - [c48]Nikki Theeuwes, Geert-Jan van Houtum, Yingqian Zhang:
Improving Ambulance Dispatching with Machine Learning and Simulation. ECML/PKDD (4) 2021: 302-318 - [c47]Vahideh Reshadat, Alp Akcay, Kalliopi Zervanou, Yingqian Zhang, Eelco de Jong:
Relation Representation Learning for Special Cargo Ontology. SSCI 2021: 1-8 - [i13]Paulo da Costa, Peter Verleijsdonk, Simon Voorberg, Alp Akcay, Stella Kapodistria, Willem van Jaarsveld, Yingqian Zhang:
Policies for the Dynamic Traveling Maintainer Problem with Alerts. CoRR abs/2105.15119 (2021) - 2020
- [j14]Murat Firat, Guillaume Crognier, Adriana F. Gabor, Cor A. J. Hurkens, Yingqian Zhang:
Column generation based heuristic for learning classification trees. Comput. Oper. Res. 116: 104866 (2020) - [j13]Juntao Gao, Yingqian Zhang:
Regular Expression Learning from Positive Examples Based on Integer Programming. Int. J. Softw. Eng. Knowl. Eng. 30(10): 1443-1479 (2020) - [j12]Paulo Roberto de Oliveira da Costa, Alp Akcay, Yingqian Zhang, Uzay Kaymak:
Remaining useful lifetime prediction via deep domain adaptation. Reliab. Eng. Syst. Saf. 195: 106682 (2020) - [c46]Reza Refaei Afshar, Yingqian Zhang, Murat Firat, Uzay Kaymak:
A State Aggregation Approach for Solving Knapsack Problem with Deep Reinforcement Learning. ACML 2020: 81-96 - [c45]Paulo R. de O. da Costa, Jason Rhuggenaath, Yingqian Zhang, Alp Akcay:
Learning 2-opt Heuristics for the Traveling Salesman Problem via Deep Reinforcement Learning. ACML 2020: 465-480 - [c44]Herbert van Leeuwen, Yingqian Zhang, Kalliopi Zervanou, Shantanu Mullick, Uzay Kaymak, Tom de Ruijter:
Lost and Found: Predicting Airline Baggage At-risk of Being Mishandled. ICAART (2) 2020: 172-181 - [c43]Jason Rhuggenaath, Paulo Roberto de Oliveira da Costa, Yingqian Zhang, Alp Akcay, Uzay Kaymak:
Dynamic Pricing Using Thompson Sampling with Fuzzy Events. IPMU (1) 2020: 653-666 - [c42]Jason Rhuggenaath, Paulo Roberto de Oliveira da Costa, Yingqian Zhang, Alp Akcay, Uzay Kaymak:
Low-Regret Algorithms for Strategic Buyers with Unknown Valuations in Repeated Posted-Price Auctions. ECML/PKDD (2) 2020: 416-436 - [c41]Reza Refaei Afshar, Yingqian Zhang, Murat Firat, Uzay Kaymak, Ali Izzet Metin, Gönenç Seçil Tarakçioglu, Cosku Bas:
Reserve price optimization with header bidding and Ad Exchange. SMC 2020: 830-835 - [c40]Jeroen Verheugd, Paulo Roberto de Oliveira da Costa, Reza Refaei Afshar, Yingqian Zhang, Sjoerd Boersma:
Predicting Water Pipe Failures with a Recurrent Neural Hawkes Process Model. SMC 2020: 2628-2633 - [c39]Robbert Reijnen, Yingqian Zhang, Wim Nuijten, Çaglar Senaras, Mariana Goldak-Altgassen:
Combining Deep Reinforcement Learning with Search Heuristics for Solving Multi-Agent Path Finding in Segment-based Layouts. SSCI 2020: 2647-2654 - [i12]Paulo R. de O. da Costa, Jason Rhuggenaath, Yingqian Zhang, Alp Akcay:
Learning 2-opt Heuristics for the Traveling Salesman Problem via Deep Reinforcement Learning. CoRR abs/2004.01608 (2020) - [i11]Jason Rhuggenaath, Alp Akcay, Yingqian Zhang, Uzay Kaymak:
Algorithms for slate bandits with non-separable reward functions. CoRR abs/2004.09957 (2020) - [i10]Reza Refaei Afshar, Yingqian Zhang, Murat Firat, Uzay Kaymak:
A State Aggregation Approach for Solving Knapsack Problem with Deep Reinforcement Learning. CoRR abs/2004.12117 (2020) - [i9]Bram Cals, Yingqian Zhang, Remco M. Dijkman, Claudy van Dorst:
Solving the Order Batching and Sequencing Problem using Deep Reinforcement Learning. CoRR abs/2006.09507 (2020)
2010 – 2019
- 2019
- [j11]Jason Rhuggenaath, Alp Akcay, Yingqian Zhang, Uzay Kaymak:
Optimal display-ad allocation with guaranteed contracts and supply side platforms. Comput. Ind. Eng. 137 (2019) - [j10]Rowan Hoogervorst, Yingqian Zhang, Gamze Tillem, Zekeriya Erkin, Sicco Verwer:
Solving bin-packing problems under privacy preservation: Possibilities and trade-offs. Inf. Sci. 500: 203-216 (2019) - [c38]Sicco Verwer, Yingqian Zhang:
Learning Optimal Classification Trees Using a Binary Linear Program Formulation. AAAI 2019: 1625-1632 - [c37]Reza Refaei Afshar, Yingqian Zhang, Murat Firat, Uzay Kaymak:
A Reinforcement Learning Method to Select Ad Networks in Waterfall Strategy. BNAIC/BENELEARN 2019 - [c36]Paulo Roberto de Oliveira da Costa, Jason Rhuggenaath, Yingqian Zhang, Alp Akcay, Wan-Jui Lee, Uzay Kaymak:
Data-Driven Policy on Feasibility Determination for the Train Shunting Problem. BNAIC/BENELEARN 2019 - [c35]Jasper Paalman, Shantanu Mullick, Kalliopi Zervanou, Yingqian Zhang:
Term Based Semantic Clusters for Very Short Text Classification. BNAIC/BENELEARN 2019 - [c34]Nikki Theeuwes, Geert-Jan van Houtum, Yingqian Zhang, Björn Gadet:
Formalization and Improvement of Ambulance Dispatching in Brabant-Zuidoost. BNAIC/BENELEARN 2019 - [c33]Sicco Verwer, Yingqian Zhang:
Learning Optimal Classification Trees Using a Binary Linear Program Formulation. BNAIC/BENELEARN 2019 - [c32]Jason Rhuggenaath, Alp Akcay, Yingqian Zhang, Uzay Kaymak:
A PSO-based Algorithm for Reserve Price Optimization in Online Ad Auctions. CEC 2019: 2611-2619 - [c31]Reza Refaei Afshar, Yingqian Zhang, Murat Firat, Uzay Kaymak:
A Decision Support Method to Increase the Revenue of Ad Publishers in Waterfall Strategy. CIFEr 2019: 1-8 - [c30]Jason Rhuggenaath, Alp Akcay, Yingqian Zhang, Uzay Kaymak:
Optimizing reserve prices for publishers in online ad auctions. CIFEr 2019: 1-8 - [c29]Jason Rhuggenaath, Alp Akcay, Yingqian Zhang, Uzay Kaymak:
Fuzzy Logic based Pricing combined with Adaptive Search for Reserve Price Optimization in Online Ad Auctions. FUZZ-IEEE 2019: 1-8 - [c28]Reza Refaei Afshar, Yingqian Zhang, Murat Firat, Uzay Kaymak:
Reinforcement Learning Method for Ad Networks Ordering in Real-Time Bidding. ICAART (Revised Selected Papers) 2019: 16-36 - [c27]Arno van de Ven, Yingqian Zhang, Wan-Jui Lee:
Boosting Local Search Using Machine Learning: A Study on Improving Local Search by Graph Classification in Determining Capacity of Shunting Yards. ICAART (Revised Selected Papers) 2019: 183-203 - [c26]Reza Refaei Afshar, Yingqian Zhang, Murat Firat, Uzay Kaymak:
A Reinforcement Learning Method to Select Ad Networks in Waterfall Strategy. ICAART (2) 2019: 256-265 - [c25]Arno van de Ven, Yingqian Zhang, Wan-Jui Lee, Rik Eshuis, Anna Wilbik:
Determining Capacity of Shunting Yards by Combining Graph Classification with Local Search. ICAART (2) 2019: 285-293 - [c24]Paulo Roberto de Oliveira da Costa, Jason Rhuggenaath, Yingqian Zhang, Alp Akcay, Wan-Jui Lee, Uzay Kaymak:
Data-Driven Policy on Feasibility Determination for the Train Shunting Problem. ECML/PKDD (3) 2019: 719-734 - [c23]Jasper Paalman, Shantanu Mullick, Kalliopi Zervanou, Yingqian Zhang:
Term Based Semantic Clusters for Very Short Text Classification. RANLP 2019: 878-887 - [c22]Dylan Rijnen, Jason Rhuggenaath, Paulo Roberto de Oliveira da Costa, Yingqian Zhang:
Machine Learning based Simulation Optimisation for Trailer Management. SMC 2019: 3687-3692 - [c21]Jason Rhuggenaath, Paulo Roberto de Oliveira da Costa, Alp Akcay, Yingqian Zhang, Uzay Kaymak:
A heuristic policy for dynamic pricing and demand learning with limited price changes and censored demand. SMC 2019: 3693-3698 - [i8]Paulo R. de O. da Costa, Jason Rhuggenaath, Yingqian Zhang, Alp Akcay, Wan-Jui Lee, Uzay Kaymak:
Data-driven Policy on Feasibility Determination for the Train Shunting Problem. CoRR abs/1907.04711 (2019) - [i7]Paulo R. de O. da Costa, Alp Akcay, Yingqian Zhang, Uzay Kaymak:
Remaining Useful Lifetime Prediction via Deep Domain Adaptation. CoRR abs/1907.07480 (2019) - [i6]Dylan Rijnen, Jason Rhuggenaath, Paulo R. de O. da Costa, Yingqian Zhang:
Machine Learning based Simulation Optimisation for Trailer Management. CoRR abs/1907.07568 (2019) - 2018
- [c20]Jason Rhuggenaath, Yingqian Zhang, Alp Akcay, Uzay Kaymak, Sicco Verwer:
Learning fuzzy decision trees using integer programming. FUZZ-IEEE 2018: 1-8 - [c19]Evertjan Peer, Vlado Menkovski, Yingqian Zhang, Wan-Jui Lee:
Shunting Trains with Deep Reinforcement Learning. SMC 2018: 3063-3068 - [i5]Murat Firat, Guillaume Crognier, Adriana F. Gabor, Yingqian Zhang, Cor A. J. Hurkens:
Constructing classification trees using column generation. CoRR abs/1810.06684 (2018) - 2017
- [j9]Sicco Verwer, Yingqian Zhang, Qing Chuan Ye:
Auction optimization using regression trees and linear models as integer programs. Artif. Intell. 244: 368-395 (2017) - [j8]Jun-Qiang Wang, Guo-qiang Fan, Yingqian Zhang, Cheng-Wu Zhang, Joseph Y.-T. Leung:
Two-agent scheduling on a single parallel-batching machine with equal processing time and non-identical job sizes. Eur. J. Oper. Res. 258(2): 478-490 (2017) - [c18]Sicco Verwer, Yingqian Zhang:
Learning Decision Trees with Flexible Constraints and Objectives Using Integer Optimization. CPAIOR 2017: 94-103 - [c17]Qing Chuan Ye, Yingqian Zhang, Uzay Kaymak:
Modeling participation behavior in repeated task allocations with fuzzy connectives. SMC 2017: 3219-3234 - 2016
- [j7]Junqiang Wang, Jian Chen, Yingqian Zhang, George Q. Huang:
Schedule-based execution bottleneck identification in a job shop. Comput. Ind. Eng. 98: 308-322 (2016) - [c16]Qing Chuan Ye, Yingqian Zhang:
Participation Behavior and Social Welfare in Repeated Task Allocations. ICA 2016: 94-97 - 2015
- [i4]Qing Chuan Ye, Yingqian Zhang, Rommert Dekker:
Fair task allocation in transportation. CoRR abs/1505.07434 (2015) - 2014
- [j6]Jelmer P. van der Gaast, Cornelius A. Rietveld, Adriana F. Gabor, Yingqian Zhang:
A Tabu Search Algorithm for application placement in computer clustering. Comput. Oper. Res. 50: 38-46 (2014) - [j5]Bart de Keijzer, Tomas B. Klos, Yingqian Zhang:
Finding Optimal Solutions for Voting Game Design Problems. J. Artif. Intell. Res. 50: 105-140 (2014) - [i3]Sicco Verwer, Yingqian Zhang, Qing Chuan Ye:
Learning optimization models in the presence of unknown relations. CoRR abs/1401.1061 (2014) - 2012
- [j4]Mathijs de Weerdt, Yingqian Zhang, Tomas Klos:
Multiagent task allocation in social networks. Auton. Agents Multi Agent Syst. 25(1): 46-86 (2012) - [c15]Sicco Verwer, Yingqian Zhang:
Revenue prediction in budget-constrained sequential auctions with complementarities. AAMAS 2012: 1399-1400 - [c14]Yingqian Zhang, Sicco Verwer:
Mechanism for Robust Procurements. PRIMA 2012: 77-91 - [i2]Bart de Keijzer, Tomas B. Klos, Yingqian Zhang:
Solving Weighted Voting Game Design Problems Optimally: Representations, Synthesis, and Enumeration. CoRR abs/1204.5213 (2012) - 2010
- [j3]Adriaan ter Mors, Chetan Yadati, Cees Witteveen, Yingqian Zhang:
Coordination by design and the price of autonomy. Auton. Agents Multi Agent Syst. 20(3): 308-341 (2010) - [c13]Bart de Keijzer, Tomas Klos, Yingqian Zhang:
Enumeration and exact design of weighted voting games. AAMAS 2010: 391-398 - [c12]Chetan Yadati, Cees Witteveen, Yingqian Zhang:
Coordinating Agents - An Analysis of Coordination in Supply-chain Management Tasks. ICAART (2) 2010: 218-223
2000 – 2009
- 2009
- [j2]Yingqian Zhang, Efrat Manisterski, Sarit Kraus, V. S. Subrahmanian, David Peleg:
Computing the fault tolerance of multi-agent deployment. Artif. Intell. 173(3-4): 437-465 (2009) - [c11]Bart de Keijzer, Sylvain Bouveret, Tomas Klos, Yingqian Zhang:
On the Complexity of Efficiency and Envy-Freeness in Fair Division of Indivisible Goods with Additive Preferences. ADT 2009: 98-110 - [c10]Yingqian Zhang, Mathijs de Weerdt:
Creating Incentives to Prevent Intentional Execution Failures. IAT 2009: 431-434 - 2008
- [c9]Mathijs de Weerdt, Yingqian Zhang:
Preventing Under-Reporting in Social Task Allocation. AMEC/TADA 2008: 1-14 - [c8]Roman van der Krogt, Mathijs de Weerdt, Yingqian Zhang:
Of Mechanism Design Multiagent Planning. ECAI 2008: 423-427 - [c7]Chetan Yadati, Cees Witteveen, Yingqian Zhang, Mengxiao Wu, Han La Poutré:
Autonomous Scheduling. FCS 2008: 73-81 - [c6]Chetan Yadati, Cees Witteveen, Yingqian Zhang, Mengxiao Wu, Han La Poutré:
Autonomous Scheduling with Unbounded and Bounded Agents. MATES 2008: 195-206 - [i1]Yingqian Zhang, Mathijs de Weerdt:
Creating incentives to prevent execution failures: an extension of VCG mechanism. Planning in Multiagent Systems 2008 - 2007
- [c5]Mathijs de Weerdt, Yingqian Zhang, Tomas Klos:
Distributed task allocation in social networks. AAMAS 2007: 76 - [c4]J. Renze Steenhuisen, Cees Witteveen, Yingqian Zhang:
Plan-Coordination Mechanisms and the Price of Autonomy. CLIMA 2007: 1-21 - 2005
- [c3]Yingqian Zhang:
Towards fault tolerance for multiagent systems. AAMAS 2005: 1387 - [p1]Jürgen Dix, Yingqian Zhang:
IMPACT: A Multi-Agent Framework with Declarative Semantics. Multi-Agent Programming 2005: 69-94 - 2004
- [c2]V. S. Subrahmanian, Sarit Kraus, Yingqian Zhang:
Distributed Algorithms for Dynamic Survivability of Multiagent Systems. CLIMA 2004: 1-15 - 2003
- [j1]Jürgen Dix, Thomas Eiter, Michael Fink, Axel Polleres, Yingqian Zhang:
Monitoring Agents using Declarative Planning. Fundam. Informaticae 57(2-4): 345-370 (2003) - [c1]Jürgen Dix, Thomas Eiter, Michael Fink, Axel Polleres, Yingqian Zhang:
Monitoring Agents Using Declarative Planning. KI 2003: 646-660
Coauthor Index
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of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-30 21:31 CET by the dblp team
all metadata released as open data under CC0 1.0 license
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since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
