| Comparison of least squares Monte Carlo methods with applications to energy real options S Nadarajah, F Margot, N Secomandi European Journal of Operational Research 256 (1), 196-204, 2017 | 117* | 2017 |
| Relaxations of approximate linear programs for the real option management of commodity storage S Nadarajah, F Margot, N Secomandi Management Science 61 (12), 3054-3076, 2015 | 92 | 2015 |
| A review of the operations literature on real options in energy S Nadarajah, N Secomandi European Journal of Operational Research 309 (2), 469-487, 2023 | 64 | 2023 |
| A level-set method for convex optimization with a feasible solution path Q Lin, S Nadarajah, N Soheili URL: http://www. optimization-online. org/DB_HTML/2017/10/6274. html, 2017 | 52 | 2017 |
| Less-than-truckload carrier collaboration problem: modeling framework and solution approach S Nadarajah, JH Bookbinder Journal of heuristics 19 (6), 917-942, 2013 | 47 | 2013 |
| Revisiting approximate linear programming: Constraint-violation learning with applications to inventory control and energy storage Q Lin, S Nadarajah, N Soheili Management Science 66 (4), 1544-1562, 2019 | 37* | 2019 |
| Meeting corporate renewable power targets A Trivella, D Mohseni-Taheri, S Nadarajah Management science 69 (1), 491-512, 2023 | 33 | 2023 |
| Merchant energy trading in a network S Nadarajah, N Secomandi Operations Research 66 (5), 1304-1320, 2018 | 32 | 2018 |
| Managing shutdown decisions in merchant commodity and energy production: A social commerce perspective A Trivella, S Nadarajah, SE Fleten, D Mazieres, D Pisinger Manufacturing and Service Operations Management, 2019 | 23* | 2019 |
| Data‐driven storage operations: Cross‐commodity backtest and structured policies C Mandl, S Nadarajah, S Minner, S Gavirneni Production and Operations Management 31 (6), 2438-2456, 2022 | 22* | 2022 |
| Offline-online reinforcement learning for energy pricing in office demand response: lowering energy and data costs D Jang, L Spangher, T Srivistava, M Khattar, U Agwan, S Nadarajah, ... Proceedings of the 8th ACM International Conference on Systems for Energy …, 2021 | 21 | 2021 |
| Relationship between least squares Monte Carlo and approximate linear programming S Nadarajah, N Secomandi Operations Research Letters 45 (5), 409-414, 2017 | 18 | 2017 |
| Deep reinforcement learning with planning guardrails for building energy demand response D Jang, L Spangher, S Nadarajah, C Spanos Energy and AI 11, 100204, 2023 | 17 | 2023 |
| A data efficient and feasible level set method for stochastic convex optimization with expectation constraints Q Lin, S Nadarajah, N Soheili, T Yang Journal of machine learning research 21 (143), 1-45, 2020 | 17 | 2020 |
| Dynamic pricing for hotel rooms when customers request multiple-day stays S Nadarajah, YF Lim, Q Ding Available at SSRN 2639188, 2015 | 16 | 2015 |
| Collaborative logistics in vehicle routing S Nadarajah University of Waterloo, 2008 | 15 | 2008 |
| Self-guided approximate linear programs: randomized multi-shot approximation of discounted cost markov decision processes P Pakiman, S Nadarajah, N Soheili, Q Lin Management science 71 (4), 3384-3404, 2025 | 14* | 2025 |
| A parameter-free and projection-free restarting level set method for adaptive constrained convex optimization under the error bound condition Q Lin, R Ma, S Nadarajah, N Soheili arXiv preprint arXiv:2010.15267, 2020 | 14 | 2020 |
| Physical vs Virtual corporate power purchase agreements: Meeting renewable targets amid demand and price uncertainty SDM Taheri, S Nadarajah, A Trivella European Journal of Operational Research 320 (1), 256-270, 2025 | 12 | 2025 |
| A machine learning approach to methane emissions mitigation in the oil and gas industry J Wang, S Nadarajah, J Wang, AP Ravikumar EarthArXiv, 2020 | 10 | 2020 |
Nicola SecomandiRice UniversityVerified email at rice.edu
