Aiko Yamashita, Oslo and Akershus University College
Abstract: In this talk, I will introduce my background and provide an overview of the research conducted in the last years within Software Quality and Maintenance; and how some of its underlying concepts/techniques could relate to sustainability challenges. I will conclude my talk with some personal views on the impact of information technology on sustainability-related initiatives and which potential areas I would like to explore within IT for Sustainability.
Followed by this virtual seminar from Princeton University at 4 p.m.
Warren B. Powell, Princeton University CASTLE Lab will be presenting the fifth seminar in the Computational Sustainability Virtual Seminar Series.
Abstract: Problems in energy and sustainability represent a rich mixture of decisions intermingled with different forms of uncertainty. These decision problems have been addressed by multiple communities from operations research (stochastic programming, Markov decision processes, simulation optimization, decision analysis), computer science, optimal control (from engineering and economics), and applied mathematics. In this talk, I will identify the major dimensions of this rich class of problems, spanning static to fully sequential problems, offline and online learning (including so-called bandit problems), derivative-free and derivative-based algorithms, with attention given to problems with expensive function evaluations. We divide solution strategies for sequential problems (dynamic programs) between stochastic search (policy search) and policies based on lookahead approximations (which include both stochastic programming as well as value functions based on Bellmans equations). We further divide each of these two fundamental solution approaches into two subclasses, producing four classes of policies for approaching sequential stochastic optimization problems. We use a simple energy storage problem to demonstrate that each of these four classes may work best, as well as opening the door to a range of hybrid policies. I will show that a single elegant framework spans all of these approaches, providing scientists with a more comprehensive toolbox for approaching the rich problems that arise in energy and sustainability.
Bio: Warren B. Powell is a professor in the Department of Operations Research and Financial Engineering at Princeton University, where he has taught since 1981 after receiving his BSE from Princeton University and Ph.D. from MIT. He is the founder and director of the laboratory for Computational Stochastic Optimization and Learning (CASTLE Labs), which spans contributions to models and algorithms in stochastic optimization, with applications to energy systems, health and medical research, and the sciences. He has two books and over 200 papers, and is working on a new book Optimization under Uncertainty: A Unified Framework.
The Computational Sustainability Virtual Seminar Series presents talks by researchers and educators in Computational Sustainability, and is being sponsored by CompSustNet, with support from the National Science Foundations Expeditions in Computing program and Cornell University. You can stay informed about the seminar series at www.compsust.net/seminar.php, where we will post upcoming talks and videos of previous talks.