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X-WR-CALNAME:Computational Optimisation Group
X-ORIGINAL-URL:http://optimisation.doc.ic.ac.uk
X-WR-CALDESC:Events for Computational Optimisation Group
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DTSTART:20110101T000000
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DTSTART;TZID=UTC:20120514T110000
DTEND;TZID=UTC:20120514T110000
DTSTAMP:20260418T174105
CREATED:20170124T102148Z
LAST-MODIFIED:20170124T102148Z
UID:605-1336993200-1336993200@optimisation.doc.ic.ac.uk
SUMMARY:Seminar: Scheduling Modular Projects on a Bottleneck Resource
DESCRIPTION:Title: Scheduling Modular Projects on a Bottleneck ResourceSpeaker: Dr. Roel Leus Affiliation: Faculty of Business and Economics of KU LeuvenLocation: Room 572A Huxley BuildingTime: 11:00am \nAbstract. In this paper\, we model a research-and-development project as consisting of several modules\, with each module containing one or more activities. We examine how to schedule the activities of such a project in order to maximize the expected profit when the activities have a probability of failure and when an activity's failure can cause its module and thereby the overall project to fail. A module succeeds when at least one of its constituent activities is successfully executed. All activities are scheduled on a scarce resource that is modeled as a single machine. We describe various policy classes\, establish the relationship between the classes\, develop exact algorithms to optimize over two different classes (one dynamic program and one branch-and-bound algorithm)\, and examine the computational performance of the algorithms on randomly generated instance sets. \nAbout the speaker. Roel Leus holds a Master's degree (1998) in Business Engineering and a PhD (2003) in Applied Economics from KU Leuven (Belgium).  He is currently Associate Professor of Operations Research at the Faculty of Business and Economics of KU Leuven.  He has been a visiting researcher at London Business School (2004) and at LAAS-CNRS Toulouse (2008).
URL:http://optimisation.doc.ic.ac.uk/event/seminar-scheduling-modular-projects-on-a-bottleneck-resource/
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BEGIN:VEVENT
DTSTART;TZID=UTC:20120515T140000
DTEND;TZID=UTC:20120515T140000
DTSTAMP:20260418T174105
CREATED:20170124T102148Z
LAST-MODIFIED:20170124T102148Z
UID:604-1337090400-1337090400@optimisation.doc.ic.ac.uk
SUMMARY:Seminar: Tutorial on Stochastic Calculus
DESCRIPTION:Title: Tutorial on Stochastic CalculusSpeaker: Florian LockerAffiliation: Institute for Statistics and Mathematics of WULocation: CPSE seminar room (C615 Roderic Hill)Time: 2:00pm \nAbstract. This tutorial session provides an introduction to stochastic calculus along the lines of the Merton model for asset pricing. Some properties of the components of this model will be explained and used to construct basic stochastic integrals. I will then proceed with the most important theorems in the general case\, notably Itō’s lemma\, and evaluate some examples. \nAbout the speaker. Florian studied economics and finance at the University of Innsbruck and Tulane University and joined the Institute for Statistics and Mathematics at WU Vienna as a PhD student in 2008. He is interested in methods concerning the hedging of derivative assets within incomplete markets and when assets exhibit jumps\, and their numerical implementation. He is currently visiting the QUADS research group at Imperial College.
URL:http://optimisation.doc.ic.ac.uk/event/seminar-tutorial-on-stochastic-calculus/
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BEGIN:VEVENT
DTSTART;TZID=UTC:20120525T140000
DTEND;TZID=UTC:20120525T140000
DTSTAMP:20260418T174105
CREATED:20170124T102148Z
LAST-MODIFIED:20170124T102148Z
UID:603-1337954400-1337954400@optimisation.doc.ic.ac.uk
SUMMARY:Seminar: On Control and Random Dynamical Systems in Reproducing Kernel Hilbert Spaces
DESCRIPTION:Title: On Control and Random Dynamical Systems in Reproducing Kernel Hilbert SpacesSpeaker: Dr. Boumediene HamziAffiliation: Department of Mathematics of Imperial CollegeLocation: CPSE seminar room (C615 Roderic Hill)Time: 2:00pm \nAbstract. We introduce a data-based approach to estimating key quantities which arise in the study of nonlinear control systems and random nonlinear dynamical systems. Our approach hinges on the observation that much of the existing linear theory may be readily extended to nonlinear systems – with a reasonable expectation of success – once the nonlinear system has been mapped into a high or infinite dimensional Reproducing Kernel Hilbert Space. In particular\, we develop computable\, non-parametric estimators approximating controllability and observability energy functions for nonlinear systems\, and study the ellipsoids they induce. It is then shown that the controllability energy estimator provides a key means for approximating the invariant measure of an ergodic\, stochastically forced nonlinear system. We also apply this approach to the problem of model reduction of nonlinear control systems.  In all cases the relevant quantities are estimated from simulated or observed data. This is joint work with J. Bouvrie (Duke University). \nAbout the speaker. Boumediene Hamzi is a Marie Curie Fellow at the Department of Mathematics of Imperial College. He obtained his Ph.D. in Control Theory from the University of Paris-Sud and then held different visiting academic positions at UCDavis\, the MSRI and then Duke University. His current research interests are the analysis of control and random dynamical systems in Reproducing Kernel Hilbert Spaces in view of developing data-based methods for the analysis and prediction of random dynamical systems and  control strategies for nonlinear systems on the basis of observed data (rather than a pre-described model).
URL:http://optimisation.doc.ic.ac.uk/event/seminar-on-control-and-random-dynamical-systems-in-reproducing-kernel-hilbert-spaces/
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