Carolina Osorio

Learn More
The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Abstract We present a dynamic network loading model that yields queue length distributions, accounts for spillbacks, and maintains a differentiable mapping from the dynamic demand on the dynamic queue lengths. The model also captures the(More)
The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. This paper proposes a simulation-based optimization (SO) method that enables the efficient use of complex stochastic urban traffic simulators to address various transportation problems. It presents a metamodel that integrates information(More)
This paper presents an analytical model, based on finite capacity queueing network theory, to evaluate congestion in protein synthesis networks. These networks are modeled as a set of single server bufferless queues in a tandem topology. This model proposes a detailed state space formulation, which provides a fine description of congestion and contributes(More)
This paper applies a computationally efficient simulation-based optimization (SO) algorithm suitable for large-scale transportation problems. The algorithm is based on a metamodel approach. The metamodel combines information from a high-resolution yet inefficient microscopic urban traffic simulator with information from a scalable and tractable analytical(More)
We consider subset selection problems in ranking and selection with tight computational budgets. We develop a new procedure that selects the best <i>m</i> out of <i>k</i> stochastic systems. Previous approaches have focused on individually separating out the top <i>m</i> from all the systems being considered. We reformulate the problem by casting all(More)
This paper presents a simulation-based optimization (SO) algorithm for nonlinear problems with general constraints and computationally expensive evaluation of objective functions. It focuses on metamodel techniques. This paper proposes an SO technique that also uses metamodel information when testing the improvement of the proposed points. We use a Bayesian(More)
C. G. Jung believed that water was a symbol for the unconscious mind, the background from where our conscious thoughts emerge, and also the sea where they melt into the dream-like state of primary processes (1). Water comprises about 80% of the brain volume and water homeostasis is inextricably coupled to the CNS function. In this regard, neuroscience(More)