Warren B. Powell

20.1k total citations · 3 hit papers
269 papers, 12.6k citations indexed

About

Warren B. Powell is a scholar working on Management Science and Operations Research, Transportation and Artificial Intelligence. According to data from OpenAlex, Warren B. Powell has authored 269 papers receiving a total of 12.6k indexed citations (citations by other indexed papers that have themselves been cited), including 80 papers in Management Science and Operations Research, 64 papers in Transportation and 62 papers in Artificial Intelligence. Recurrent topics in Warren B. Powell's work include Transportation Planning and Optimization (64 papers), Transportation and Mobility Innovations (38 papers) and Vehicle Routing Optimization Methods (38 papers). Warren B. Powell is often cited by papers focused on Transportation Planning and Optimization (64 papers), Transportation and Mobility Innovations (38 papers) and Vehicle Routing Optimization Methods (38 papers). Warren B. Powell collaborates with scholars based in United States, United Kingdom and Slovakia. Warren B. Powell's co-authors include Yosef Sheffi, Peter I. Frazier, Gregory A. Godfrey, Savaş Dayanik, Jennie Si, Andrew G. Barto, Hugo Simão, Don Wunsch, Hüseyin Topaloğlu and Ilya O. Ryzhov and has published in prestigious journals such as Nature, Physical Review Letters and Nucleic Acids Research.

In The Last Decade

Warren B. Powell

265 papers receiving 11.9k citations

Hit Papers

Approximate Dynamic Progr... 2004 2026 2011 2018 2011 2007 2004 400 800 1.2k

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Warren B. Powell 3.0k 2.6k 2.6k 2.4k 2.3k 269 12.6k
George L. Nemhauser 9.5k 3.1× 3.1k 1.2× 2.4k 0.9× 1.7k 0.7× 2.5k 1.1× 199 22.7k
Thomas L. Magnanti 3.5k 1.2× 1.4k 0.6× 2.0k 0.8× 1.0k 0.4× 645 0.3× 92 10.9k
James B. Orlin 3.3k 1.1× 1.0k 0.4× 2.0k 0.8× 578 0.2× 1.5k 0.7× 156 12.4k
Hanif D. Sherali 3.2k 1.1× 2.2k 0.8× 3.6k 1.4× 528 0.2× 596 0.3× 360 13.0k
Pierre Hansen 7.0k 2.3× 1.5k 0.6× 925 0.4× 1.1k 0.4× 3.5k 1.5× 456 17.1k
Bart De Schutter 2.1k 0.7× 10.5k 4.0× 3.8k 1.4× 2.5k 1.0× 2.6k 1.1× 701 19.2k
Laurence A. Wolsey 7.1k 2.3× 2.5k 0.9× 2.4k 0.9× 454 0.2× 2.3k 1.0× 156 17.7k
Richard F. Hartl 6.5k 2.1× 876 0.3× 663 0.3× 3.3k 1.4× 1.3k 0.6× 232 11.6k
Pãnos M. Pardalos 4.4k 1.4× 2.0k 0.8× 1.7k 0.7× 504 0.2× 2.7k 1.2× 516 15.0k
Mitsuo Gen 7.8k 2.6× 3.1k 1.2× 1.1k 0.4× 577 0.2× 3.0k 1.3× 400 16.3k

Countries citing papers authored by Warren B. Powell

Since Specialization
Citations

This map shows the geographic impact of Warren B. Powell's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Warren B. Powell with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Warren B. Powell more than expected).

Fields of papers citing papers by Warren B. Powell

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Warren B. Powell. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Warren B. Powell. The network helps show where Warren B. Powell may publish in the future.

Co-authorship network of co-authors of Warren B. Powell

This figure shows the co-authorship network connecting the top 25 collaborators of Warren B. Powell. A scholar is included among the top collaborators of Warren B. Powell based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Warren B. Powell. Warren B. Powell is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Tian, Zhili, et al.. (2021). Adaptive Learning of Drug Quality and Optimization of Patient Recruitment for Clinical Trials with Dropouts. Manufacturing & Service Operations Management. 24(1). 580–599. 8 indexed citations
2.
Huang, Yixiao, Lei Zhao, Warren B. Powell, Tong Yue, & Ilya O. Ryzhov. (2019). Optimal Learning for Urban Delivery Fleet Allocation. Transportation Science. 53(3). 623–641. 22 indexed citations
3.
Ryzhov, Ilya O., et al.. (2019). Bayesian Exploration for Approximate Dynamic Programming. Operations Research. 67(1). 198–214. 5 indexed citations
4.
Liu, Han, et al.. (2016). A lasso-based sparse knowledge gradient policy for sequential optimal learning. International Conference on Artificial Intelligence and Statistics. 417–425. 1 indexed citations
5.
Wang, Yingfei, Chu Wang, & Warren B. Powell. (2016). The knowledge gradient for sequential decision making with stochastic binary feedbacks. International Conference on Machine Learning. 1138–1147. 5 indexed citations
6.
Coulon, Michael, Javad Khazaei, & Warren B. Powell. (2015). SMART-SREC: A Stochastic Model of the New Jersey Solar Renewable Energy Certificate Market. SSRN Electronic Journal.
7.
Powell, Warren B. & Ilya O. Ryzhov. (2012). Optimal Learning. Wiley series in probability and statistics. 113 indexed citations
8.
Mes, Martijn, Warren B. Powell, & Peter I. Frazier. (2011). Hierarchical Knowledge Gradient for Sequential Sampling. Journal of Machine Learning Research. 12(10). 2931–2974. 66 indexed citations
9.
Ryzhov, Ilya O., et al.. (2011). May the best man win: simulation optimization for match-making in e-sports. Winter Simulation Conference. 4239–4250. 2 indexed citations
10.
Hannah, Lauren A., Warren B. Powell, & David M. Blei. (2010). Nonparametric Density Estimation for Stochastic Optimization with an Observable State Variable. Neural Information Processing Systems. 23. 820–828. 21 indexed citations
11.
Ryzhov, Ilya O., et al.. (2010). Optimal learning of transition probabilities in the two-agent newsvendor problem. Winter Simulation Conference. 1088–1098. 4 indexed citations
12.
Scott, Warren R., Warren B. Powell, & Hugo Simão. (2010). Calibrating simulation models using the knowledge gradient with continuous parameters. Winter Simulation Conference. 1099–1109. 2 indexed citations
13.
Ryzhov, Ilya O. & Warren B. Powell. (2009). A Monte Carlo knowledge gradient method for learning abatement potential of emissions reduction technologies. Winter Simulation Conference. 1492–1502. 5 indexed citations
14.
Dayanik, Savaş, Warren B. Powell, & Kazutoshi Yamazaki. (2008). Index policies for discounted bandit problems with availability constraints. Advances in Applied Probability. 40(2). 377–400. 8 indexed citations
15.
Powell, Warren B.. (2008). Approximate dynamic programming: lessons from the field. Winter Simulation Conference. 205–214. 9 indexed citations
16.
George, Abraham, Warren B. Powell, & Sanjeev R. Kulkarni. (2008). Value Function Approximation using Multiple Aggregation for Multiattribute Resource Management. Journal of Machine Learning Research. 9(68). 2079–2111. 32 indexed citations
17.
Powell, Warren B.. (2003). Dynamic Models of Transportation Operations.. Supply Chain Management An International Journal. 677–756. 2 indexed citations
18.
Powell, Warren B., et al.. (1990). APPLICATION OF OPTIMIZATION BASED MODELS ON VEHICLE ROUTING AND SCHEDULING PROBLEMS WITH TIME WINDOW CONSTRAINTS. Journal of Business Logistics. 11(2). 7 indexed citations
19.
Powell, Warren B., et al.. (1988). SENSITIVITY ANALYSIS OF DYNAMIC NETWORKS: AN APPLICATION TO PRICING AND LOAD EVALUATION FOR TRUCKLOAD MOTOR CARRIERS. 1 indexed citations
20.
Sheffi, Yosef, Hani S. Mahmassani, & Warren B. Powell. (1981). Evacuation studies for nuclear power plant sites: A new challenge for transportation engineers. ITE journal. 51(6). 25–28. 21 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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