BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//ALOP - ECPv5.2.0//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:ALOP
X-ORIGINAL-URL:https://alop.uni-trier.de
X-WR-CALDESC:Events for ALOP
BEGIN:VTIMEZONE
TZID:Europe/Berlin
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20210328T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20211031T010000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20211115T160000
DTEND;TZID=Europe/Berlin:20211115T170000
DTSTAMP:20211016T132802
CREATED:20210519T085624Z
LAST-MODIFIED:20210521T050924Z
UID:5608-1636992000-1636995600@alop.uni-trier.de
SUMMARY:ALOP-Colloquium with Sungho Shin\, University of Wisconsin-Madison
DESCRIPTION:On Monday\, November 15\, 2021\, at 16:00 c.t.\, Ph.D. candidate Sungho Shin\, University of Madison-Wisonsin will speak about his recent work: \n \nTitle: Graph-Structured Nonlinear Programming: Properties and Algorithms \n \nA graph-structured nonlinear program (NLP) is a nonlinear optimization problem whose algebraic structure is induced by a graph. These problems arise in diverse applications such as dynamic optimization (model predictive control and moving horizon estimation)\, network optimization (energy systems and supply chain)\, optimization with embedded discretized partial differential equations\, and multi-stage stochastic programming. Building upon the existing NLP sensitivity theory\, we show that the nodal solution sensitivity against parametric perturbation decays exponentially with respect to the distance from the perturbation point. Remarkably\, this result (which we call exponential decay of sensitivity; EDS) holds under fairly standard regularity assumptions used in classical NLP sensitivity theory: second-order sufficiency conditions and the linear independence constraint qualification. EDS allows the creation of novel computing strategies\, the overlapping Schwarz decomposition method (also known as domain decomposition). This method decomposes a graph-structured NLP into multiple smaller subproblems over overlapping subdomains and solves the subproblems in parallel and iteratively with the exchange of information at boundries. Based on the EDS result\, we prove that for a certain class of problems satisfying the regularity assumptions\, the convergence rate of the overlapping Schwarz method improves exponentially with the size of overlap; thus\, overlap accelerates the convergence. With real-world case studies on gas and electric networks\, we demonstrate the effectiveness of the overlapping Schwarz method. \n \nThis presentation will take place via ZOOM. A link will be e-mailed prior to the event
URL:https://alop.uni-trier.de/event/alop-colloquium-with-sungho-shin-university-of-wisconsin-madison/
CATEGORIES:Colloquium
ORGANIZER;CN="RTG%20ALOP%20at%20Trier%20University":MAILTO:ALOP@uni-trier.de
END:VEVENT
END:VCALENDAR