On Mathematical Programming (ISMP 2015), the Most Important Meeting of the Mathematical Optimization Society (MOS)
Total Page：16
File Type：pdf, Size：1020Kb
Load more
Recommended publications
-
Industrial Engineering and Management Sciences
FALL 2018 INDUSTRIAL ENGINEERING AND MANAGEMENT SCIENCES IEMS TRANSFORMS ADVISING AND MENTORING FOR UNDERGRADUATES New ‘GuIdE’ advising and mentoring system strengthens student connections to faculty, peers, and alumni oo often, advising and group luncheons with a small group of mentoring meetings students and one faculty member mentor, and offer an environment for students reduce to discussions to ask questions, learn from their peers, on what courses to take and develop a connection to faculty that encourages additional conversations Tin upcoming academic quarters. Marita Labedz Poll throughout the year. A 2016-17 survey of students in Central to the department’s curriculum Northwestern Engineering’s Department redesign is Marita Labedz Poll, who of Industrial Engineering and Management joined the department in fall 2017 as an Sciences (IEMS) and anecdotal feedback academic adviser. Labedz Poll’s past from IEMS alumni reveal that many former experience includes serving as associate students wish they had taken advantage vice chancellor for student affairs and Advice from Marita Labedz Poll more fully of all that Northwestern has dean of students at the University of to undergraduate students: to offer, including the opportunity to learn Massachusetts, Boston, senior associate I always recommend that students from and interact with faculty outside dean of students at Lake Forest College, follow their interests and be the classroom. and assistant director of residence life at intentional about what they To increase the department’s focus on the University of Rochester. engage in, inside and outside of the faculty mentoring for its undergraduates, In 2018-19, IEMS will expand its classroom. Take time once a year IEMS introduced a new advising model roster of GuIdEs for undergraduates ‘‘to consider your opportunities in 2017-18. -
INFORMS OS Today 4(1)
INFORMS OS Today The Newsletter of the INFORMS Optimization Society Volume 4 Number 1 May 2014 Contents Chair's Column ............................. 1 Chair's Column Nominations for OS Prizes ................. 28 Nominations for OS Officers ............... 29 Sanjay Mehrotra Industrial Engineering and Management Sciences Host Sought for the 2016 OS Conference ....29 Department, Northwestern University [email protected] Featured Articles My Nonlinear (Non-Straight) Optimization Path Donald Goldfarb . .3 Optimization is now becoming a household Looking Back at My Life word in communities across engineering, man- Alexander Shapiro . 10 agement, health and other areas of scientific re- search. I recall an advice from my department Adding Squares: From Control Theory to Opti- chairman when I came up for tenure over twenty mization years ago: `You need to explain in layman terms Pablo Parrilo . 14 the nature of optimization research, and demon- A Branch-and-Cut Decomposition Algorithm strate its use in practice. The promotion and for Solving Chance-Constrained Mathematical tenure committee is full of bench scientists, and Programs with Finite Support they don't understand what we do'. Hard work James R. Luedtke . 20 and persistence from our community members have lead in establishing optimization as a \core Sparse Recovery in Derivative-Free Optimization technology." The goal in front of us is to es- Afonso Bandeira . .24 tablish our leadership as drivers of research that changes the life of the common man. This is hard, since it requires simultaneous thinking in deep mathematical terms, as we all like to do, and in broad applied terms. However, I hope that the time to come will bring optimizers and optimization technology to new heights. -
Chordal Graphs and Semidefinite Optimization
Full text available at: http://dx.doi.org/10.1561/2400000006 Chordal Graphs and Semidefinite Optimization Lieven Vandenberghe University of California, Los Angeles [email protected] Martin S. Andersen Technical University of Denmark [email protected] Boston — Delft Full text available at: http://dx.doi.org/10.1561/2400000006 Foundations and Trends R in Optimization Published, sold and distributed by: now Publishers Inc. PO Box 1024 Hanover, MA 02339 United States Tel. +1-781-985-4510 www.nowpublishers.com [email protected] Outside North America: now Publishers Inc. PO Box 179 2600 AD Delft The Netherlands Tel. +31-6-51115274 The preferred citation for this publication is L. Vandenberghe and M. S. Andersen. Chordal Graphs and Semidefinite Optimization. Foundations and Trends R in Optimization, vol. 1, no. 4, pp. 241–433, 2014. R This Foundations and Trends issue was typeset in LATEX using a class file designed by Neal Parikh. Printed on acid-free paper. ISBN: 978-1-68083-039-2 c 2015 L. Vandenberghe and M. S. Andersen All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, mechanical, photocopying, recording or otherwise, without prior written permission of the publishers. Photocopying. In the USA: This journal is registered at the Copyright Clearance Cen- ter, Inc., 222 Rosewood Drive, Danvers, MA 01923. Authorization to photocopy items for internal or personal use, or the internal or personal use of specific clients, is granted by now Publishers Inc for users registered with the Copyright Clearance Center (CCC). -
ISMP BP Front
Conference Program 1 TABLE OF CONTENTS Welcome from the Chair . 2 Schedule of Daily Events & Sessions . 3 20TH INTERNATIONAL SYMPOSIUM ON Speaker Information . 5 MATHEMATICAL PROGRAMMING August 23-28, 2009 Social Events & Excursions . 6 Chicago, Illinois, USA Internet Access . 7 Opening Session & Prizes . 8 Area Map . 9 PROGRAM ORGANIZING COMMITTEE COMMITTEE Exhibitors . 10 Chair Mihai Anitescu John R. Birge Argonne National Lab Plenary & Semi-Plenary Sessions . 12 University of Chicago USA Track Schedule . 17 USA John R. Birge Karen Aardal University of Chicago Floor Plans & Maps . 22 Centrum Wiskunde & USA Informatica Michael Ferris Cluster Chairs . 24 The Netherlands University of Wisconsin- Michael Ferris Madison Technical Sessions University of Wisconsin- USA Monday . 25 Madison Jeff Linderoth USA University of Wisconsin- Tuesday . 49 Michael Goemans Madison Wednesday . 74 Massachusetts Institute of USA Thursday . 98 Technology Todd Munson USA Argonne National Lab Friday . 121 Michael Jünger USA Universität zu Köln Jorge Nocedal Session Chair Index . 137 Germany Northwestern University Masakazu Kojima USA Author Index . 139 Tok yo Institute of Technology Jong-Shi Pang Session Index . 147 Japan University of Illinois at Urbana- Rolf Möhring Champaign Advertisers Technische Universität Berlin USA World Scientific . .150 Germany Stephen J. Wright Andy Philpott University of Wisconsin- IOS Press . .151 University of Auckland Madison OptiRisk Systems . .152 New Zealand USA Claudia Sagastizábal Taylor & Francis . .153 CEPEL LINDO Systems . .154 Brazil Springer . .155 Stephen J. Wright University of Wisconsin- Mosek . .156 Madison USA Sponsors . Back Cover Yinyu Ye Stanford University USA 2 Welcome from the Chair On behalf of the Organizing Committee and The University of Chicago, I The University of Chicago welcome you to ISMP 2009, the 20th International Symposium on Booth School of Business Mathematical Programming. -
OPTIMIZATION MODELS for SHAPE-CONSTRAINED FUNCTION ESTIMATION PROBLEMS INVOLVING NONNEGATIVE POLYNOMIALS and THEIR RESTRICTIONS by DAVID´ PAPP
OPTIMIZATION MODELS FOR SHAPE-CONSTRAINED FUNCTION ESTIMATION PROBLEMS INVOLVING NONNEGATIVE POLYNOMIALS AND THEIR RESTRICTIONS by DAVID´ PAPP A Dissertation submitted to the Graduate School-New Brunswick Rutgers, The State University of New Jersey in partial fulfillment of the requirements for the degree of Doctor of Philosophy Graduate Program in Operations Research written under the direction of Dr. Farid Alizadeh and approved by New Brunswick, New Jersey May 2011 ABSTRACT OF THE DISSERTATION Optimization models for shape-constrained function estimation problems involving nonnegative polynomials and their restrictions by DAVID´ PAPP Dissertation Director: Dr. Farid Alizadeh In this thesis function estimation problems are considered that involve constraints on the shape of the estimator or some other underlying function. The function to be estimated is assumed to be continuous on an interval, and is approximated by a polynomial spline of given degree. First the estimation of univariate functions is considered under constraints that can be represented by the nonnegativity of affine functionals of the estimated function. These include bound constraints, monotonicity, convexity and concavity constraints. A general framework is presented in which arbitrary combination of such constraints, along with monotonicity and periodicity constraints, can be modeled and handled in a both theoretically and practically efficient manner, using second-order cone programming and semidefinite programming. The approach is illustrated by a variety of applications in statistical estimation. Wherever possible, the numerical results are compared to those obtained using methods previously proposed in the statistical literature. Next, multivariate problems are considered. Shape constraints that are tractable in the uni- variate case are intractable in the multivariate setting. -
Accelerating Conditional Gradient Methods Thomas Kerdreux
Accelerating conditional gradient methods Thomas Kerdreux To cite this version: Thomas Kerdreux. Accelerating conditional gradient methods. Optimization and Control [math.OC]. Université Paris sciences et lettres, 2020. English. NNT : 2020UPSLE002. tel-03052834 HAL Id: tel-03052834 https://tel.archives-ouvertes.fr/tel-03052834 Submitted on 10 Dec 2020 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Préparée à l’École Normale Supérieure Accelerating Conditional Gradient Methods Soutenue par Composition du jury : Thomas Kerdreux Francis Bach Le 30 Juin 2020 Researcher, INRIA Paris Président Zaid Harchaoui Associate Professor, University of Washington Rapporteur École doctorale no386 Mikael Johansson École Doctorale De Sci- Professor, KTH Rapporteur ences Mathématiques de Paris Martin Jaggi Assistant Professor, EPFL Examinateur Sebastian Pokutta Spécialité Professor, Technische Universität Berlin Examinateur Mathématiques Ap- Alexandre d’Aspremont pliquées Researcher, CNRS Directeur de thèse "Chacune de ces machines, d’une manière ou d’une autre, ajoute à la puissance matérielle de l’homme, c’est-à-dire à sa capacité dans le bien comme dans le mal." Georges Bernanos, La France contre les robots. i À ma mère et à mon père pour leur amour. ii Résumé Les méthodes de Gradient Conditionnel, ou algorithmes de Frank-Wolfe, sont des méthodes itératives du premier ordre utiles pour résoudre des problèmes d’optimisation sous contraintes. -
UCLA Electronic Theses and Dissertations
UCLA UCLA Electronic Theses and Dissertations Title Operator Splitting Methods for Convex and Nonconvex Optimization Permalink https://escholarship.org/uc/item/78q0n13c Author Liu, Yanli Publication Date 2020 Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California UNIVERSITY OF CALIFORNIA Los Angeles Operator Splitting Methods for Convex and Nonconvex Optimization A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Mathematics by Yanli Liu 2020 c Copyright by Yanli Liu 2020 ABSTRACT OF THE DISSERTATION Operator Splitting Methods for Convex and Nonconvex Optimization by Yanli Liu Doctor of Philosophy in Mathematics University of California, Los Angeles, 2020 Professor Wotao Yin, Chair This dissertation focuses on a family of optimization methods called operator split- ting methods. They solve complicated problems by decomposing the problem structure into simpler pieces and make progress on each of them separately. Over the past two decades, there has been a resurgence of interests in these methods as the demand for solving structured large-scale problems grew. One of the major challenges for split- ting methods is their sensitivity to ill-conditioning, which often makes them struggle to achieve a high order of accuracy. Furthermore, their classical analyses are restricted to the nice settings where solutions do exist, and everything is convex. Much less is known when either of these assumptions breaks down. This work aims to address the issues above. Specifically, we propose a novel acceler- ation technique called inexact preconditioning, which exploits second-order information at relatively low computation cost. We also show that certain splitting methods still work on problems without solutions, in the sense that their iterates provide information on what goes wrong and how to fix. -
Tuesday Schedule
20th International Symposium on Mathematical Programming TA02 Tuesday, 10:30am - 12:00pm ■ TA01 Marriott - Chicago A Geometric Methods for Approximation Algorithms Cluster: Approximation Algorithms Invited Session Chair: Cliff Stein, Columbia University, 326 S W Mudd Building, 500 W. 120th Street, New York, NY, 10027, [email protected] 1 - Geometric Rounding: Theory and Application Dongdong Ge, Stanford University, Terman 328, Stanford, 94305, United States of America, [email protected], Jiawei Zhang, Yinyu Ye We develop a new dependent randomized rounding method for approximation of optimization problems with integral assignment constraints. The core of the method is a simple, intuitive, and computationally efficient geometric rounding that simultaneously rounds multiple points in a multi-dimensional simplex to its vertices. Using this method we obtain in a systematic way known as well as new results for a series of combinatorial optimization problems. 2 - Understanding the Limits of Semidefinite Programming through Unique Games Prasad Raghavendra, University of Washington, #4, 5856 Alderson Street, Pittsburgh, PA, 15217, United States of America, [email protected], David Steurer Assuming the Unique games conjecture (UGC), recent work has demonstrated that a simple semidefinite programming relaxation yields the best approximation for large classes of combinatorial optimization problems like constraint satisfaction problems. In this work, we show that irrespective of the truth of UGC, introducing additional constraints