E
Efstratios N. Pistikopoulos
Researcher at Texas A&M University
Publications - 627
Citations - 21326
Efstratios N. Pistikopoulos is an academic researcher from Texas A&M University. The author has contributed to research in topics: Model predictive control & Optimization problem. The author has an hindex of 65, co-authored 603 publications receiving 18831 citations. Previous affiliations of Efstratios N. Pistikopoulos include University College London & Imperial College London.
Papers
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The explicit linear quadratic regulator for constrained systems
TL;DR: A technique to compute the explicit state-feedback solution to both the finite and infinite horizon linear quadratic optimal control problem subject to state and input constraints is presented, and it is shown that this closed form solution is piecewise linear and continuous.
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Environmentally conscious long-range planning and design of supply chain networks
TL;DR: In this paper, a mathematical programming-based methodology is presented for the explicit inclusion of life cycle assessment (LCA) criteria as part of the strategic investment decisions related to the design and planning of supply chain networks.
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Optimal design of dynamic systems under uncertainty
TL;DR: In this article, a unified process design framework for obtaining integrated process and control systems design, which are economically optimal and can cope with parametric uncertainty and process disturbances, is described.
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A two-stage stochastic programming model for the optimal design of distributed energy systems
TL;DR: A two-stage stochastic programming model used to solve the optimization problem with genetic algorithm performing the search on the first stage variables and a Monte Carlo method dealing with uncertainty in the second stage is proposed.
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A rolling horizon optimization framework for the simultaneous energy supply and demand planning in microgrids
Javier Silvente,Georgios M. Kopanos,Georgios M. Kopanos,Efstratios N. Pistikopoulos,Efstratios N. Pistikopoulos,Antonio Espuña +5 more
TL;DR: In this article, the main novelty is the simultaneous management of energy production and energy demand within a reactive scheduling approach to deal with the presence of uncertainty associated to production and consumption, where delays in nominal energy demands are allowed under associated penalty costs to tackle flexible and fluctuating demand profiles.