Abstract: This paper presents a multistage stochastic programming formulation of a transmission-constrained economic dispatch subject to multiarea renewable production uncertainty, with a focus on ...
Abstract: This paper presents a computation-efficient stochastic dynamic programming algorithm for solving energy storage price arbitrage considering variable charge and discharge efficiencies. We ...
This study develops a unified framework for optimal portfolio selection in jump–uncertain stochastic markets, contributing both theoretical foundations and computational insights. We establish the ...
Without resorting to dynamic programming, we determine the decumulation strategy for the holder of a defined contribution pension plan. We formulate this as a constrained stochastic optimal control ...
ABSTRACT: Offline reinforcement learning (RL) focuses on learning policies using static datasets without further exploration. With the introduction of distributional reinforcement learning into ...
Developmental programming involves the accurate conversion of signalling levels and dynamics to transcriptional outputs. The transcriptional relay in the Notch pathway relies on nuclear complexes ...
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Dr. Katehakis is a distinguished professor at Rutgers University and chair of the Department of Management Science & Information Systems. He holds a courtesy appointment in Rutgers' New Brunswick ...
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