An Empirical Analysis of Bike Sharing Usage and Rebalancing: Evidence from Barcelona and Seville A Faghih-Imani, RC Hampshire, L Marla, N Eluru Transportation Research - Part A 97, 177-191, 2017 | 281 | 2017 |
Integrated disruption management and flight planning to trade off delays and fuel burn L Marla, B Vaaben, C Barnhart Transportation Science 51 (1), 88-111, 2017 | 119 | 2017 |
An efficient simulation-based approach to ambulance fleet allocation and dynamic redeployment Y Yue, L Marla, R Krishnan Proceedings of the AAAI Conference on Artificial Intelligence 26 (1), 398-405, 2012 | 118 | 2012 |
An analysis of bike sharing usage: Explaining trip generation and attraction from observed demand RC Hampshire, L Marla 91st Annual meeting of the transportation research board, Washington, DC, 12 …, 2012 | 103 | 2012 |
Dynamic Airline Disruption Management under Airport Operating Uncertainty J Lee, L Marla, A Jacquillat Transportation Science 54 (4), 973-997, 2020 | 70* | 2020 |
Robust optimization: Lessons learned from aircraft routing L Marla, V Vaze, C Barnhart Computers and Operations Research 98, 165-184, 2018 | 68 | 2018 |
How to Incorporate Monotonicity in Deep Networks While Preserving Flexibility? A Gupta, N Shukla, L Marla, A Kolbeinsson, K Yellepeddi Workshop on Machine Learning with Guarantees at NeurIPS 2019, 2019 | 61 | 2019 |
Dynamic pricing for airline ancillaries with customer context N Shukla, A Kolbeinsson, K Otwell, L Marla, K Yellepeddi Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 52 | 2019 |
Estimating Economic Losses from Cyber-Attacks on Shipping Ports: An Optimization-Based Approach G Weaver, L Marla, B Feddersen, D Wei, A Rose, M van Moer Transportation Research Part C 137, 103423, 2022 | 25 | 2022 |
Vehicle routing problem with time windows: A deterministic annealing approach M Baranwal, PM Parekh, L Marla, SM Salapaka, CL Beck 2016 American Control Conference (ACC), 790-795, 2016 | 15 | 2016 |
Robust optimization for network-based resource allocation problems under uncertainty L Marla Massachusetts Institute of Technology, 2007 | 14 | 2007 |
Galactic Air Improves Ancillary Revenues with Dynamic Personalized Pricing A Kolbeinsson, N Shukla, A Gupta, L Marla, K Yellepeddi INFORMS Journal on Applied Analytics 52 (3), 233-249, 2022 | 12* | 2022 |
Airline OR innovations soar during COVID-19 recovery LA Garrow, V Lurkin, L Marla Operations Research Forum 3 (1), 14, 2022 | 12 | 2022 |
The impact of climate change on the recoverability of airline networks J Lee, L Marla, P Vaishnav Transportation Research Part D: Transport and Environment 95, 102801, 2021 | 12 | 2021 |
Distribution Shift in Airline Customer Behavior during COVID-19 A Garg, N Shukla, L Marla, S Somanchi arXiv preprint arXiv:2111.14938, 2021 | 11 | 2021 |
Managing EMS systems with user abandonment in emerging economies L Marla, K Krishnan, S Deo IISE Transactions 53 (4), 389-406, 2021 | 10 | 2021 |
Robust ambulance allocation using risk-based metrics K Krishnan, L Marla, Y Yue 2016 8th International Conference on Communication Systems and Networks …, 2016 | 10 | 2016 |
Robust Modeling and Planning: Insights from Three Industrial Applications L Marla, A Rikun, G Stauffer, E Pratsini Operations Research Perspectives, 100150, 2020 | 9* | 2020 |
From Average Customer to Individual Traveler: A Field Experiment in Airline Ancillary Pricing N Shukla, A Kolbeinsson, L Marla, K Yellepeddi Available at SSRN 3518854, 2020 | 8 | 2020 |
Adaptive Model Selection Framework: An Application to Airline Pricing N Shukla, A Kolbeinsson, L Marla, K Yellepeddi arXiv preprint arXiv:1905.08874, 2019 | 8 | 2019 |