C
Carolina Osorio
Researcher at Massachusetts Institute of Technology
Publications - 63
Citations - 1314
Carolina Osorio is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: Simulation-based optimization & Queueing theory. The author has an hindex of 16, co-authored 60 publications receiving 1055 citations. Previous affiliations of Carolina Osorio include HEC Montréal & Google.
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An analytic finite capacity queueing network model capturing the propagation of congestion and blocking
Carolina Osorio,Michel Bierlaire +1 more
TL;DR: An analytic queueing network model which preserves the finite capacity of the queues and uses structural parameters to grasp the between-queue correlation and is applied to study patient flow in a network of units of the Geneva University Hospital.
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A simulation-based optimization framework for urban transportation problems
Carolina Osorio,Michel Bierlaire +1 more
TL;DR: A simulation-based optimization method that enables the efficient use of complex stochastic urban traffic simulators to address various transportation problems is proposed and a metamodel that integrates information from a simulator with an analytical queueing network model is presented.
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A Computationally Efficient Simulation-Based Optimization Algorithm for Large-Scale Urban Transportation Problems
Carolina Osorio,Linsen Chong +1 more
TL;DR: A computationally efficient simulation-based optimization SO algorithm suitable to address large-scale generally constrained urban transportation problems, based on a novel metamodel formulation that systematically and efficiently identifies signal plans with improved average city-wide travel times is proposed.
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Urban transportation emissions mitigation: Coupling high-resolution vehicular emissions and traffic models for traffic signal optimization
Carolina Osorio,Kanchana Nanduri +1 more
TL;DR: It is shown that the analytical structural information provided by macroscopic analytical emissions models can contribute, despite their lower-resolution, to enhance the computational efficiency of algorithms that embed higher-resolution inefficient emissions models.
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Energy-Efficient Urban Traffic Management: A Microscopic Simulation-Based Approach
Carolina Osorio,Kanchana Nanduri +1 more
TL;DR: A methodology that combines a stochastic microscopic traffic simulation model with an instantaneous vehicular fuel consumption model is proposed and applied to a network in the Swiss city of Lausanne, where it outperforms traditional methodologies.