BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Computational Optimisation Group - ECPv6.15.11//NONSGML v1.0//EN CALSCALE:GREGORIAN METHOD:PUBLISH X-WR-CALNAME:Computational Optimisation Group X-ORIGINAL-URL:http://optimisation.doc.ic.ac.uk X-WR-CALDESC:Events for Computational Optimisation Group REFRESH-INTERVAL;VALUE=DURATION:PT1H X-Robots-Tag:noindex X-PUBLISHED-TTL:PT1H BEGIN:VTIMEZONE TZID:UTC BEGIN:STANDARD TZOFFSETFROM:+0000 TZOFFSETTO:+0000 TZNAME:UTC DTSTART:20120101T000000 END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTART;TZID=UTC:20130214T110000 DTEND;TZID=UTC:20130214T110000 DTSTAMP:20260508T072511 CREATED:20170124T102145Z LAST-MODIFIED:20170124T102145Z UID:589-1360839600-1360839600@optimisation.doc.ic.ac.uk SUMMARY:Seminar: Time Consistency in Multistage Stochastic Optimization DESCRIPTION:Title: Time Consistency in Multistage Stochastic OptimizationSpeaker: Prof. Georg PflugAffiliation: Department of Statistics and Operations Research – University of Vienna Location: CPSE seminar room (C615 Roderic Hill)Time: 11:00am \nAbstract. A fundamental principle for dynamic optimization is Bellman’s priciple\, stating that at any initially optimal decision sequence is also optimal at later stages. This time-consistency principle is still valid for stochastic programs if the criterion is to minimze expected costs or to maximize expeted profits. However\, as simple examples show\, it is not longer valid\, if risk-sensitive criteria are chosen such as the optimization of the average value at risk. It turns out that most risk functionals are time inconsistent\, e.g.\, it may happen that today some loss distribution appears to be less risky than another\, but looking at the conditional distribution at a later time\, the opposite relation holds. We demonstrate that this time inconsistency disappears if the conditional functionals are defined in an extended manner\, i.e.\, are evaluated under a specific change of measure. It follows from our results that\, for consistency reasons\, the revelation of partial information in time must dramatically change a decision maker's preferences among the remaining courses of action to keep time consistency. We extend conditional risk functionals to allow a temporal decomposition of the initial risk functional in time consistent way. With this extension\, a Bellmann priciple may be proved. Counterexamples show that without change of measures the only time consistent risk functionals are the expectation and the essential supremum. \nAbout the speaker. \nBorn on June 10th\, 1951 in Vienna. Study of Law\, Mathematics and Statistics at the University of Vienna\, Magister iuris (1974)\, Ph.D in Mathematics (1976). Assistant Professor University of Vienna (1976-81). Professor\, University of Giessen\, Germany (1981-1989). Full Professor\, University of Vienna (1989 – ). \n \nVisting Professor at the University of Bayreuth (1979)\, Michigan State University (1985)\, University of California Davis (1993)\, Universite de Rennes (1994)\, Technion Haifa\, Israel (1996)\, Princeton University (2001)\, University of California Davis (2006). \n \nDean\, Department of Mathematics\, University of Giessen\, Germany (1987-88); Dean\, Faculty of Business\, Economics and Statistics\, University of Vienna\, Austria (2008-2010); Head\, Department of Statistics and Decision Support Systems\, University of Vienna (2000-2003); Member of Senate\, University of Vienna (200-2003); Research scholar\, International Institute of Applied Systems Analysis\, IIASA (1990 – ) – Risk\, Modelling and Society (RMS)\, Risk and Vulnerability Project (RAV)\, . \n \nEditor in chief: Statistics and Decisions\, Central European Journal of Operations Research \n \nAssociate editor: Statistics and Probability Letters (1994-2007)\, Stochastic Programming Electronic Publication Series\, Austrian Journal of Statistics\, Mathematics of Operations Research (1994 – 1997)\, Mathematical Methods of OR\, Computational Optimization and Applications\, Computational Management Science\, Energy Systems: Optimization\, Modeling\, Simulation and Economic Aspects; Vestnik of the Finance Academy\, Moscow. \n \nMember\, Council of Scientists\, INTAS\, Bruessel (1999 – 2002); Fellow\, International Statistical Institute; Member\, executive board of the international committee on stochastic programming; Member\, central research council\, University of Bolzano/Bozen. \n \nAuthor Author of 4books\, editor of 5 books\, and more than 70 publications in refereed journals\, such as: Annals of Statistics\, Annals of OR\, Probability Theory\, J Statist. Planning and Inference\, J. ACM\, Parallel Computing\, The Computer Journal\, Math. Programming\, Mathematics of Optimization\, SIAM J. on Optimization\, Computational Optimization and Applications\, J. Applied Probability\, Stoch. Processes and Applications\, Graphs and Combinatorics\, J. Theoretical Computer Science\, Quantitative Finance etc. \n \nOrganizer of COMETT II Workshop "Simulation and Optimization"\, Raach (1992); Workshop"Computer Intensive Methods in Simulation and Optimization"\, IIASA (1994); EURO Winter School "Stochastic Optimization"\, Semmering (1996); Fourth World Congress of the Bernoulli Society\, Vienna (1996); Workshop Stochastic Dynamic Optimization\, IIASA (2002); Workshop series "Mathematical Optimization for Financial Models"\, Semmering (2003)\, Cyprus (2003)\, Bergamo (2004); 11th International Conference on Stochastic Programming\, Vienna (2007); APMOD\, Vienna and Bratislava (2008). \n \nProject leader of past and present projects: Project leader of past and present projects: Statistical pattern recognition (Austrian National Bank); Pension fund management (BVP pension fund); Data dependency in financial optimization (FWF- Austrian Science Fund); Optimal network design and marketing strategies (Telekom Austria); AURORA-Advanced parallel and distributed algorithms for Computational Finance (FWF); Unit life insurance with guarantee (Austrian National Bank); WEBOPT (European Commission-subproject leader)\, Risk management in liberalized electricity markets (WWTF); Seeds in Finance (Austrian National Bank)\, RISKPLAN (Asia-Link)\, Long-term risk management (FWF)\, Pension fund management (Bridge Program). URL:http://optimisation.doc.ic.ac.uk/event/seminar-time-consistency-in-multistage-stochastic-optimization/ END:VEVENT BEGIN:VEVENT DTSTART;TZID=UTC:20130220T150000 DTEND;TZID=UTC:20130220T150000 DTSTAMP:20260508T072511 CREATED:20170124T102144Z LAST-MODIFIED:20170124T102144Z UID:588-1361372400-1361372400@optimisation.doc.ic.ac.uk SUMMARY:Seminar: Applications and Beyond DESCRIPTION:Title: Applications and BeyondSpeaker: Amit M. ManthanwarAffiliation: On Industrial Process Automation and Control TheoryLocation: CPSE seminar room (C615 Roderic Hill)Time: 3:00pm \nAbstract. At the end of second millennia advent of the technology of Model Predictive Control (MPC) has revolutionized the way process industry is controlled and operated. This technological breakthrough for industrial process automation asks the much sought-after control objective question\, how to attain desired profit margins while satisfying all the conditions of feasibility\, stability\, operability\, performance and safety from plants operating under the influence of uncertainty? Towards answering this question\, first generation of MPC development was focused on the various regulation types of issues. Next\, we focused on the development of MPC tuning engine that drives the dynamic economics of process control–delivering true economic value of control strategy. Now in the second generation of its evolution questions are raised on how MPC could be administered to the applications having fast dynamics (e.g.\, fuel cells\, automobile and biomedical applications) or systems to which on-line implementation of MPC is expensive or not possible. This has lead to the development of off-line (explicit) implementation of MPC via –you-solve-only-once– multi-parametric optimisation techniques. In this new role of MPC-on-a-chip\, we aim to develop robust control algorithms and tools for nonlinear systems operating under uncertainty. Using these tools and underlined computer-aided technologies of process automation we can minimise use of energy\, minimise exploitation of environment and maximise the economic profit incentives that are consistently demanded from modern industrial plants while operating at their optimal performance and safety conditions. In this seminar we will present historical developments and major milestones in modern control theory. Furthermore\, a theoretical perspective and computational challenges to account for uncertainty in process operation for various classes of nonlinear systems will be outlined. From the practical application standpoint\, we will present a generic control automation framework for fuel cell system and its integrated subsystems. To achieve this objective a fully integrated state-of-the-art process automation laboratory for fuel cell system is developed. This testing and validation facility will be used for characterising various designs as well as benchmarking control policies of the polymer electrolyte membrane fuel cell system. Finally\, we will present how the proposed control platform will be able to communicate with the integrated subsystems at the different length-time scales while improving operational performance of fuel cell system by guaranteeing efficiency\, material stability and longevity. As a concluding remark we will highlight our vision and goal of this research program so as to contribute significantly to the knowledge while fostering new technological discoveries in the area of process systems engineering by symbiotic\, synergetic and sustainable development of industrial process automation technology. \nAbout the speaker. Amit received his Master's Degree in Chemical Engineering from Illinois Institute of Technology\, Chicago. He worked as a senior distributed control systems engineer and automation consultant with RasGas in Qatar before joining Invensys as a Software Technology Developer for Advanced Process Performance Suit and Model Predictive Control product 'Connoisseur™'. He was Lecturer and Assistant Professor at the College of Engineering\, Pune. Currently he is working with Professor Efstratios N. Pistikopoulos at the Centre for Process Systems Engineering at Imperial College London. His research is focused on the development of economically and environmentally conscious process design\, global optimisation and robust control theory. His research work carried out in collaboration with Professor Donald J. Chmielewski has been incorporated in the book titled: 'Smart Process Plants: Software and Hardware Solutions for Accurate Data and Profitable Operations'. He has published 7 scientific papers with G-index 3 and H-index 2. He is a recipient of Hamid Arastoopour Excellence in Teaching Award at Illinois Institute of Technology\, Chicago and is listed in 2006 Marquis Who's who in Science and Engineering. He is a recipient of IChemE Journals' 2011 Best Reviewers Award. URL:http://optimisation.doc.ic.ac.uk/event/seminar-applications-and-beyond/ END:VEVENT END:VCALENDAR