Abstract: Long-term hydropower operation is a complex optimization problem, as the uncertainty of natural inflow should be considered. Sampling stochastic dynamic programming (SSDP) is a method that ...

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 ...

Dr. Ramakrishnan's core research interests are in nonlinear, stochastic dynamic systems and control and their applications. Focusing on theoretical and computational analyses, he is an author or ...

Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China Engineering Research Center of Process ...

ABSTRACT: Offline reinforcement learning (RL) focuses on learning policies using static datasets without further exploration. With the introduction of distributional reinforcement learning into ...

Functional programming, as the name implies, is about functions. While functions are part of just about every programming paradigm, including JavaScript, a functional programmer has unique ...

DecisionProgramming.jl is a Julia package for solving multi-stage decision problems under uncertainty, modeled using influence diagrams. Internally, it relies on mathematical optimization. Decision ...