| A markov chain approximation to choice modeling J Blanchet, G Gallego, V Goyal Operations Research 64 (4), 886-905, 2016 | 310 | 2016 |
| On the power and limitations of affine policies in two-stage adaptive optimization D Bertsimas, V Goyal Mathematical programming 134 (2), 491-531, 2012 | 212 | 2012 |
| Mnl-bandit: A dynamic learning approach to assortment selection S Agrawal, V Avadhanula, V Goyal, A Zeevi Operations Research 67 (5), 1453-1485, 2019 | 204* | 2019 |
| Near-optimal algorithms for capacity constrained assortment optimization A Désir, V Goyal, J Zhang Available at SSRN 2543309, 2014 | 140 | 2014 |
| Thompson sampling for the mnl-bandit S Agrawal, V Avadhanula, V Goyal, A Zeevi Conference on learning theory, 76-78, 2017 | 112 | 2017 |
| Near-optimal algorithms for the assortment planning problem under dynamic substitution and stochastic demand V Goyal, R Levi, D Segev Operations Research 64 (1), 219-235, 2016 | 112 | 2016 |
| Constrained assortment optimization under the markov chain–based choice model A Désir, V Goyal, D Segev, C Ye Management Science 66 (2), 698-721, 2020 | 108* | 2020 |
| On the power of robust solutions in two-stage stochastic and adaptive optimization problems D Bertsimas, V Goyal Mathematics of Operations Research 35 (2), 284-305, 2010 | 104 | 2010 |
| How to pay, come what may: Approximation algorithms for demand-robust covering problems K Dhamdhere, V Goyal, R Ravi, M Singh 46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05), 367-376, 2005 | 102 | 2005 |
| A geometric characterization of the power of finite adaptability in multistage stochastic and adaptive optimization D Bertsimas, V Goyal, XA Sun Mathematics of Operations Research 36 (1), 24-54, 2011 | 84 | 2011 |
| MIP reformulations of the probabilistic set covering problem A Saxena, V Goyal, MA Lejeune Mathematical programming 121 (1), 1-31, 2010 | 81 | 2010 |
| Robust Markov decision process: Beyond rectangularity V Goyal, J Grand-Clement arXiv preprint arXiv:1811.00215, 2018 | 73* | 2018 |
| A PTAS for the chance-constrained knapsack problem with random item sizes V Goyal, R Ravi Operations Research Letters 38 (3), 161-164, 2010 | 64 | 2010 |
| A tight characterization of the performance of static solutions in two-stage adjustable robust linear optimization D Bertsimas, V Goyal, BY Lu Mathematical Programming 150 (2), 281-319, 2015 | 56 | 2015 |
| Sparse process flexibility designs: Is the long chain really optimal? A Désir, V Goyal, Y Wei, J Zhang Operations Research 64 (2), 416-431, 2016 | 55 | 2016 |
| Online assortment optimization with reusable resources XY Gong, V Goyal, GN Iyengar, D Simchi-Levi, R Udwani, S Wang Management Science 68 (7), 4772-4785, 2022 | 53 | 2022 |
| Improved approximations for two-stage min-cut and shortest path problems under uncertainty D Golovin, V Goyal, V Polishchuk, R Ravi, M Sysikaski Mathematical Programming 149 (1-2), 167-194, 2015 | 45* | 2015 |
| On the approximability of adjustable robust convex optimization under uncertainty D Bertsimas, V Goyal Mathematical Methods of Operations Research 77, 323-343, 2013 | 41 | 2013 |
| Capacitated assortment optimization: Hardness and approximation A Désir, V Goyal, J Zhang Operations Research 70 (2), 893-904, 2022 | 37 | 2022 |
| On the optimality of affine policies for budgeted uncertainty sets O El Housni, V Goyal Mathematics of Operations Research 46 (2), 674-711, 2021 | 36 | 2021 |
Antoine DesirINSEADVerified email at insead.edu
