Mostrando 10 resultados de: 31
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Computers and Chemical Engineering(5)
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scopus(31)
Computational and economic limitations of dispatch operations in the next-generation power grid
Conference ObjectAbstract: We study the interactions between computational and economic performance of dispatch operations undePalabras claves:Autores:Botterud A., Constantinescu E., Víctor M. Zavala, Wang J.Fuentes:scopusAn asynchronous decomposition algorithm for security constrained unit commitment under contingency events
Conference ObjectAbstract: We present a parallel and asynchronous decomposition algorithm for solving security constrained unitPalabras claves:Asynchronous parallel computing, Dual decomposition, Security-constrained unit commitmentAutores:Anitescu M., Kim K., Víctor M. ZavalaFuentes:scopusA Parallel Decomposition Scheme for Solving Long-Horizon Optimal Control Problems
Conference ObjectAbstract: We present a temporal decomposition scheme for solving long-horizon optimal control problems. The tiPalabras claves:Autores:Faulwasser T., Shin S., Víctor M. Zavala, Zanon M.Fuentes:scopusA Stochastic Dual Dynamic Programming Framework for Multiscale MPC<sup>⁎</sup>
Conference ObjectAbstract: We derive and interpret stochastic dual dynamic programming (SDDP) from the perspective of MPC to arPalabras claves:duality, energy systems, MPC, multiscale, stochastic dynamic programmingAutores:Drees K.H., Elbsat M.N., Ellis M.J., Kumar R., Víctor M. Zavala, Wenzel M.J.Fuentes:scopusA dynamic penalty approach to state constraint handling in deep reinforcement learning
ArticleAbstract: Deep reinforcement learning (RL) has emerged as a promising approach to solving sequential optimizatPalabras claves:Constraint handling, Dynamic penalty, Penalty approach, reinforcement learningAutores:Lee J.H., Víctor M. Zavala, Yoo H.Fuentes:scopusA dynamic penalty function approach for constraint-handling in reinforcement learning
Conference ObjectAbstract: Reinforcement learning (RL) is attracting attention as an effective way to solve sequential optimizaPalabras claves:Constraints, Dynamic penalty, Penalty approach, reinforcement learningAutores:Lee J.H., Víctor M. Zavala, Yoo H.Fuentes:scopusA fast moving horizon estimation algorithm based on nonlinear programming sensitivity
ArticleAbstract: Moving horizon estimation (MHE) is an efficient optimization-based strategy for state estimation. DePalabras claves:Estimation algorithms, Large-scale, nonlinear programming, real-time, Sensitivity AnalysisAutores:Biegler L.T., Laird C.D., Víctor M. ZavalaFuentes:scopusA machine learning framework for the analysis and pbkp_rediction of catalytic activity from experimental data
ArticleAbstract: We present a machine learning framework to explore the pbkp_redictability limits of catalytic activiPalabras claves:Catalysis, Data Analysis, High-dimensional, Machine learning, pbkp_redictabilityAutores:Dumesic J., Huber G.W., Keane A., Smith A.D., Víctor M. ZavalaFuentes:scopusA scalable design of experiments framework for optimal sensor placement
ArticleAbstract: We present a scalable design of an experiments framework for sensor placement in systems described bPalabras claves:Estimation, Scalable, sensor data, Sensor placementAutores:Anitescu M., Víctor M. Zavala, Yu J.Fuentes:scopusADAM: A web platform for graph-based modeling and optimization of supply chains
ArticleAbstract: Modeling and optimization are essential tasks that arise in the analysis and design of supply chainsPalabras claves:Graph Theory, Optimization, supply chain, Web toolsAutores:Göreke D., Hu Y., Martin M., Martín-Hernández E., Ruiz-Mercado G.J., Shen M., Tominac P.A., Víctor M. Zavala, Zhang W.Fuentes:scopus