Tay, T., Osorio, C. (forthcoming) A sampling strategy for high-dimensional simulation-based transportation optimization problems, Transportation Science
Vishnoi, S., Tsogsuren, I., Arora, N., Osorio, C. (2023) On the use of abundant road speed data for travel demand calibration of urban traffic simulators. ACM SIGSPATIAL '23: Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems
Zhou, T., Fields, E., and Osorio, C. (2023) A data-driven discrete simulation-based optimization algorithm for car-sharing service design Transportation Research Part B 178:102818
Tay, T., and Osorio, C. (2022) Bayesian optimization techniques for high-dimensional transportation problems Transportation Research Part B 164:210-243
Mladenov,M., Ganapathy, S., Hsu, C.W., Arora, N., Tomkins, A., Boutilier, C., and Osorio, C. (2022) An adversarial variational inference approach for travel demand calibration of urban traffic simulators. ACM SIGSPATIAL ’22, Proceedings of the International Conference on Advances in Geographic Information Systems.
Lu, J. and Osorio, C. (2022) On the analytical probabilistic modeling of flow transmission across nodes in transportation networks Transportation Research Record 2676(12):209-225
Osorio, C., and Atastoy, B. (2021) Efficient simulation-based toll optimization for large-scale networks Transportation Science 55(5):1010-1024
Fields, E., Osorio, C., Zhou, T. (2021) A data-driven method for reconstructing a distribution from a truncated sample with an application to inferring car-sharing demand Transportation Science 55 (3):616-636
Osorio, C. (2019) High-dimensional offline origin-destination (OD) demand calibration for stochastic traffic simulators of large-scale urban networks, Transportation Research Part B 124:18-43
Chen., X., Osorio C. and Santos, B. (2019). Simulation-based travel time reliable signal control, Transportation Science 53(2):523-544
Osorio C. and Punzo, V. (2019). Efficient calibration of microscopic car-following models for large-scale stochastic network models, Transportation Research Part B 119:156-173.
Osorio C. (2019). Dynamic origin-destination matrix calibration for large-scale network simulators, Transportation Research Part C 98:186-206.
Lu, J. and Osorio, C. (2018). A probabilistic traffic-theoretic network loading model suitable for large-scale network analysis, Transportation Science 52(6):1509-1530
Chong, L. and Osorio, C. (2018). A simulation-based optimization algorithm for dynamic large-scale urban transportation problems, Transportation Science 52(3):637-656.
Flötteröd, G. and Osorio C. (2017). Stochastic network link transmission model, Transportation Research Part B 102:180-209.
Osorio, C., and Selvam, K. (2017). Simulation-based optimization: achieving computational efficiency through the use of multiple simulators, Transportation Science 51(2):395-411.
Osorio, C., and Yamani, J. (2017). Analytical and scalable analysis of transient tandem Markovian finite capacity queueing networks, Transportation Science 51(3):823-840.
Zhang, C., Osorio C., and Flötteröd, G. (2017). Efficient calibration techniques for large-scale traffic simulators, Transportation Research Part B 97:214-239.
Osorio, C., and Wang, C. (2017). On the analytical approximation of joint aggregate queue-length distributions for traffic networks: a stationary finite capacity Markovian network approach, Transportation Research Part B 95:305-339.
Osorio, C., and Nanduri, K. (2015). Urban transportation emissions mitigation: coupling high-resolution vehicular emissions and traffic models for traffic signal optimization, Transportation Research Part B 81:520-538.
Osorio, C., and Chong, L. (2015). A computationally efficient simulation-based optimization algorithm for large-scale urban transportation problems, Transportation Science 49(3):623-636.
Osorio, C., and Nanduri, K. (2015). Energy-efficient urban traffic management: a microscopic simulation-based approach,Transportation Science 49(3):637-651.
Osorio, C., and Flötteröd, G. (2015). Capturing dependency among link boundaries in a stochastic dynamic network loading model, Transportation Science 49(2):420-431.
Osorio, C., and Bierlaire, M. (2013). A simulation-based optimization framework for urban transportation problems,Operations Research 61(6):1333-1345.
Osorio, C., and Bierlaire, M. (2012). A tractable analytical model for large-scale congested protein synthesis networks, European Journal of Operational Research 219(3):588-597.
Osorio, C., Flötteröd, G., and Bierlaire, M. (2011). Dynamic network loading: a differentiable model that derives link state distributions, Transportation Research Part B, 45(9):1410-1423.
Osorio, C., and Bierlaire, M. (2009). An analytic finite capacity queueing network model capturing the propagation of congestion and blocking, European Journal of Operational Research196(3):996-1007.
Osorio, C., Weibel, C., Perez, P., Bierlaire, M., and Garnerin, Ph. (2006). Patient flow simulation as a tool for estimating policy impact, Swiss Medical Informatics 58:33-36.