ISMP BP Front
Total Page：16
File Type：pdf, Size：1020Kb
Load more
Recommended publications
-
Algorithmic System Design Under Consideration of Dynamic Processes
Algorithmic System Design under Consideration of Dynamic Processes Vom Fachbereich Maschinenbau an der Technischen Universit¨atDarmstadt zur Erlangung des akademischen Grades eines Doktors der Ingenieurwissenschaften (Dr.-Ing.) genehmigte Dissertation vorgelegt von Dipl.-Phys. Lena Charlotte Altherr aus Karlsruhe Berichterstatter: Prof. Dr.-Ing. Peter F. Pelz Mitberichterstatter: Prof. Dr. rer. nat. Ulf Lorenz Tag der Einreichung: 19.04.2016 Tag der m¨undlichen Pr¨ufung: 24.05.2016 Darmstadt 2016 D 17 Vorwort des Herausgebers Kontext Die Produkt- und Systementwicklung hat die Aufgabe technische Systeme so zu gestalten, dass eine gewünschte Systemfunktion erfüllt wird. Mögliche System- funktionen sind z.B. Schwingungen zu dämpfen, Wasser in einem Siedlungsgebiet zu verteilen oder die Kühlung eines Rechenzentrums. Wir Ingenieure reduzieren dabei die Komplexität eines Systems, indem wir dieses gedanklich in überschaubare Baugruppen oder Komponenten zerlegen und diese für sich in Robustheit und Effizienz verbessern. In der Kriegsführung wurde dieses Prinzip bereits 500 v. Chr. als „Teile und herrsche Prinzip“ durch Meister Sun in seinem Buch „Die Kunst der Kriegsführung“ beschrieben. Das Denken in Schnitten ist wesentlich für das Verständnis von Systemen: „Das wichtigste Werkzeug des Ingenieurs ist die Schere“. Das Zusammenwirken der Komponenten führt anschließend zu der gewünschten Systemfunktion. Während die Funktion eines technischen Systems i.d.R. nicht verhan- delbar ist, ist jedoch verhandelbar mit welchem Aufwand diese erfüllt wird und mit welcher Verfügbarkeit sie gewährleistet wird. Aufwand und Verfügbarkeit sind dabei gegensätzlich. Der Aufwand bemisst z.B. die Emission von Kohlendioxid, den Energieverbrauch, den Materialverbrauch, … die „total cost of ownership“. Die Verfügbarkeit bemisst die Ausfallzeiten, Lebensdauer oder Laufleistung. Die Gesell- schaft stellt sich zunehmend die Frage, wie eine Funktion bei minimalem Aufwand und maximaler Verfügbarkeit realisiert werden kann. -
(+232 Lbs ) KINGS of the RING WORLD SERIES
OPEN SUPER HEAVYWEIGHT +105 kg (+232 lbs ) Japanese boxing - Shootboxing rules Super world champion Date, Place VACANT 14 World champion Date, Place VACANT Thai boxing - Full muaythai rules Thai boxing - International muaythai rules SUPER WORLD CHAMPION Date, Place SUPER WORLD CHAMPION Date, place VACANT VACANT WORLD CHAMPION Date, Place WORLD CHAMPION Date, Place 09.02.2008 LLOYD VAN DAMS ( NL ) 29.05.2004 TONY GREGORY ( FRA ) Auckland- = 289 pts Venice-ITA = 413 pts NZ OPBU EURO-AFRICAN CHAMPION Date, Place OPBU EURO-AFRICAN CHAMPION Date, Place VACANT VACANT Japanese boxing - K -1 rules Japanese boxing - Oriental Kick rules SUPER WORLD CHAMPION Date, Place SUPER WORLD CHAMPION Date, Place VACANT VACANT WORLD CHAMPION Date, Place WORLD CHAMPION Date, Place VACANT VACANT OPBU EURO-AFRICAN CHAMPION Date, Place OPBU EURO-AFRICAN CHAMPION Date, Place VACANT VACANT KINGS OF THE RING WORLD SERIES WIPU ORIENTAL PRO BOXING RULES SUPER WORLD CHAMPION Date, place VACANT e-mail : [email protected] mobile phone : +385 98 421 300 www.wipu-kings.com OPEN SUPER HEAVYWEIGHT +105 kg (+232 lbs ) 1. Semmy Schilt ( NL ) = 964 pts 2. Peter Aerts ( NL ) = 645 pts 3. Jerome Lebanner ( FRA ) = 571 pts 4. Alistar Overeem ( NL ) = 524 pts 5. Alexei Ignashov ( BLR ) = 432 pts 6. Daniel Ghita ( ROM ) = 362 pts 7. '' MIGHTY MO '' Siligia ( USA ) = 362 pts 8. Anderson '' Bradock '' Silva ( BRA ) = 344 pts 9. Mladen Brestovac ( CRO ) = 311 pts 10. Ismael Londt ( NL ) = 290 pts 11. Rico Verhoeven ( NL ) = 275 pts 12. Ben Edwards ( AUS ) = 258 pts 13. Peter Graham ( AUS ) = 243 pts 14. Alexandre Pitchkounov ( RUS ) = 236 pts 15. -
54 OP08 Abstracts
54 OP08 Abstracts CP1 Dept. of Mathematics Improving Ultimate Convergence of An Aug- [email protected] mented Lagrangian Method Optimization methods that employ the classical Powell- CP1 Hestenes-Rockafellar Augmented Lagrangian are useful A Second-Derivative SQP Method for Noncon- tools for solving Nonlinear Programming problems. Their vex Optimization Problems with Inequality Con- reputation decreased in the last ten years due to the com- straints parative success of Interior-Point Newtonian algorithms, which are asymptotically faster. In the present research We consider a second-derivative 1 sequential quadratic a combination of both approaches is evaluated. The idea programming trust-region method for large-scale nonlin- is to produce a competitive method, being more robust ear non-convex optimization problems with inequality con- and efficient than its ”pure” counterparts for critical prob- straints. Trial steps are composed of two components; a lems. Moreover, an additional hybrid algorithm is defined, Cauchy globalization step and an SQP correction step. A in which the Interior Point method is replaced by the New- single linear artificial constraint is incorporated that en- tonian resolution of a KKT system identified by the Aug- sures non-accent in the SQP correction step, thus ”guiding” mented Lagrangian algorithm. the algorithm through areas of indefiniteness. A salient feature of our approach is feasibility of all subproblems. Ernesto G. Birgin IME-USP Daniel Robinson Department of Computer Science Oxford University [email protected] -
Prizes and Awards Session
PRIZES AND AWARDS SESSION Wednesday, July 12, 2021 9:00 AM EDT 2021 SIAM Annual Meeting July 19 – 23, 2021 Held in Virtual Format 1 Table of Contents AWM-SIAM Sonia Kovalevsky Lecture ................................................................................................... 3 George B. Dantzig Prize ............................................................................................................................. 5 George Pólya Prize for Mathematical Exposition .................................................................................... 7 George Pólya Prize in Applied Combinatorics ......................................................................................... 8 I.E. Block Community Lecture .................................................................................................................. 9 John von Neumann Prize ......................................................................................................................... 11 Lagrange Prize in Continuous Optimization .......................................................................................... 13 Ralph E. Kleinman Prize .......................................................................................................................... 15 SIAM Prize for Distinguished Service to the Profession ....................................................................... 17 SIAM Student Paper Prizes .................................................................................................................... -
On Mathematical Programming (ISMP 2015), the Most Important Meeting of the Mathematical Optimization Society (MOS)
TABLE OF CONTENTS i PROGRAM COMMITTEE LOCAL ORGANIZING COMMITTEE Welcome from the Chair ii Chair Chair Schedule of Daily Events and Sessions iii Gérard P. Cornuéjols François Margot Carnegie Mellon University Carnegie Mellon University Cluster Chairs v USA Speaker Information vi Egon Balas Egon Balas Carnegie Mellon University Internet Access vii Carnegie Mellon University USA Lorenz T. Biegler Conference Mobile App vii Carnegie Mellon University Xiaojun Chen Where to go for Lunch vii The Hong Kong Polytechnic University Gérard P. Cornuéjols Opening Ceremony & Reception viii China Carnegie Mellon University Conference Cruise & Banquet ix Monique Laurent Iganacio E. Grossmann CWI Amsterdam Carnegie Mellon University Plenary & Semi-Plenary Lectures x The Netherlands John Hooker Exhibitors xv Sven Leyffer Carnegie Mellon University Master Track Schedules xvii Argonne National Laboratory USA Fatma Kilinç-Karzan Floor Plans xxii Carnegie Mellon University Arkadi Nemirovski Georgia Institute of Technology Javier F. Peña USA Carnegie Mellon University Technical Sessions 1 Monday 1 Jorge Nocedal Oleg A. Prokopyev Northwestern University University of Pittsburgh Tuesday 41 USA Kirk Pruhs Wednesday 71 Andrzej Ruszczy´nski University of Pittsburgh Rutgers University Thursday 101 USA Nikolaos V. Sahinidis Friday 140 Carnegie Mellon University Claudia Sagastizábal IMPA Rio de Janeiro (Visiting Researcher) Andrew J. Schaefer Brazil University of Pittsburgh Session Chair Index 168 David P. Williamson Michael A. Trick Author Index 170 Cornell University Carnegie Mellon University Session Index 180 USA Willem-Jan van Hoeve Laurence Wolsey Carnegie Mellon University Université Catholique de Louvain Belgium ii WELCOME FROM THE CHAIR Tepper School of Business Carnegie Mellon University 5000 Forbes Ave Pittsburgh, PA 15213-3890 It is a pleasure to welcome you to the 22nd International Symposium on Mathematical Programming (ISMP 2015), the most important meeting of the Mathematical Optimization Society (MOS). -
A Review on the Performance of Linear and Mixed Integer Two-Stage Stochastic Programming Algorithms and Software
Noname manuscript No. (will be inserted by the editor) A Review on the Performance of Linear and Mixed Integer Two-Stage Stochastic Programming Algorithms and Software Juan J. Torres · Can Li · Robert M. Apap · Ignacio E. Grossmann Received: date / Accepted: date Abstract This paper presents a tutorial on the state-of-the-art methodologies for the solution of two-stage (mixed-integer) linear stochastic programs and provides a list of software designed for this purpose. The methodologies are classified according to the decomposition alternatives and the types of the vari- ables in the problem. We review the fundamentals of Benders Decomposition, Dual Decomposition and Progressive Hedging, as well as possible improve- ments and variants. We also present extensive numerical results to underline the properties and performance of each algorithm using software implemen- tations including DECIS, FORTSP, PySP, and DSP. Finally, we discuss the strengths and weaknesses of each methodology and propose future research directions. Keywords Stochastic programming · L-shaped method · Scenario Decom- position · Software benchmark Juan J. Torres Universit´eParis 13, Sorbonne Paris Cit´e,LIPN, CNRS, (UMR 7030), France E-mail: torresfi[email protected] Can Li Department of Chemical Engineering, Carnegie Mellon University, 5000 Forbes Ave, Pitts- burgh, PA 15213, USA E-mail: [email protected] Robert M. Apap Department of Chemical Engineering, Carnegie Mellon University, 5000 Forbes Ave, Pitts- burgh, PA 15213, USA Ignacio E. Grossmann Department of Chemical Engineering, Carnegie Mellon University, 5000 Forbes Ave, Pitts- burgh, PA 15213, USA E-mail: [email protected] 2 Juan J. Torres et al. 1 Introduction In the modeling and optimization of real-world problems, there is usually a level of uncertainty associated with the input parameters and their future outcomes. -
Mathematics People
NEWS Mathematics People Tardos Named Goldfarb and Nocedal Kovalevsky Lecturer Awarded 2017 von Neumann Éva Tardos of Cornell University Theory Prize has been chosen as the 2018 AWM- SIAM Sonia Kovalevsky Lecturer by Donald Goldfarb of Columbia the Association for Women in Math- University and Jorge Nocedal of ematics (AWM) and the Society for Northwestern University have been Industrial and Applied Mathematics awarded the 2017 John von Neu- (SIAM). She was honored for her “dis- mann Theory Prize by the Institute tinguished scientific contributions for Operations Research and the to the efficient methods for com- Management Sciences (INFORMS). binatorial optimization problems According to the prize citation, “The Éva Tardos on graphs and networks, and her award recognizes the seminal con- work on issues at the interface of tributions that Donald Goldfarb computing and economics.” According to the prize cita- Jorge Nocedal and Jorge Nocedal have made to the tion, she is considered “one of the leaders in defining theory and applications of nonlinear the area of algorithmic game theory, in which algorithms optimization over the past several decades. These contri- are designed in the presence of self-interested agents butions cover a full range of topics, going from modeling, governed by incentives and economic constraints.” With to mathematical analysis, to breakthroughs in scientific Tim Roughgarden, she was awarded the 2012 Gödel Prize computing. Their work on the variable metric methods of the Association for Computing Machinery (ACM) for a paper “that shaped the field of algorithmic game theory.” (BFGS and L-BFGS, respectively) has been extremely in- She received her PhD in 1984 from Eötvös Loránd Univer- fluential.” sity. -
Introduction of the Class of 2020
National Academy of Engineering October 4, 2020 CLASS OF 2020 Members and International Members CLASS OF 2020 MEMBERS Class of 2020: Members In February 2020 the members of the NAE elected 86 new members and 18 new international members. Election to the NAE is one of the highest professional distinctions conferred on engineers. The main criteria for membership in the National Academy of Engineering are outstanding personal contributions and accomplishments in one or both of the following categories: 1. Engineering research, practice, or education, including, where appropriate, significant contributions to the engineering literature. 2020 2. Pioneering of new and developing fields of technology, making major advancements in traditional fields of engineering, or MEMBERS developing/implementing innovative approaches to engineering education, or providing engineering leadership of major endeavors. The following pages feature the names, photographs, and election citations of each newly elected member and international member. The numbers following their names denote primary and secondary NAE section affiliations. Dr. Lilia A. Abron (4) Dr. Saeed D. Barbat (10) President and Chief Executive Officer Executive Technical Leader Safety, Policy, and CLASS OF PEER Consultants, P.C. Vehicle Analytical Tools Ford Motor Company For leadership in providing technology-driven sustainable housing and environmental For leadership in automotive safety and engineering solutions in the United States and contributions to the science of crashworthiness, South Africa. occupant protection, and biomechanics. Ms. Eleanor J. Allen (4) Dr. Peter J. Basser (2) Chief Executive Officer NIH Senior Investigator Water for People Section on Quantitative Imaging & Tissue Sciences For leadership and advocacy in making clean National Institutes of Health National Institute of water and sanitation systems accessible to Child Health and Human Development people around the world. -
Basic Polyhedral Theory 3
BASIC POLYHEDRAL THEORY VOLKER KAIBEL A polyhedron is the intersection of finitely many affine halfspaces, where an affine halfspace is a set ≤ n H (a, β)= x Ê : a, x β { ∈ ≤ } n n n Ê Ê for some a Ê and β (here, a, x = j=1 ajxj denotes the standard scalar product on ). Thus, every∈ polyhedron is∈ the set ≤ n P (A, b)= x Ê : Ax b { ∈ ≤ } m×n of feasible solutions to a system Ax b of linear inequalities for some matrix A Ê and some m ≤ n ′ ′ ∈ Ê vector b Ê . Clearly, all sets x : Ax b, A x = b are polyhedra as well, as the system A′x = b∈′ of linear equations is equivalent{ ∈ the system≤ A′x }b′, A′x b′ of linear inequalities. A bounded polyhedron is called a polytope (where bounded≤ means− that≤ there − is a bound which no coordinate of any point in the polyhedron exceeds in absolute value). Polyhedra are of great importance for Operations Research, because they are not only the sets of feasible solutions to Linear Programs (LP), for which we have beautiful duality results and both practically and theoretically efficient algorithms, but even the solution of (Mixed) Integer Linear Pro- gramming (MILP) problems can be reduced to linear optimization problems over polyhedra. This relationship to a large extent forms the backbone of the extremely successful story of (Mixed) Integer Linear Programming and Combinatorial Optimization over the last few decades. In Section 1, we review those parts of the general theory of polyhedra that are most important with respect to optimization questions, while in Section 2 we treat concepts that are particularly relevant for Integer Programming. -
1. Introduction: Learning About Operations Research
1. Introduction: Learning about Operations Research IRV LUSTIG: So hi, my name's Irv Lustig from Princeton Consultants and today, I'm privileged to interview George Nemhauser, who is currently a distinguished professor at the Georgia Institute of Technology. So thank you, George, for joining us today and let's get started. GEORGE NEMHAUSER: Oh, you're most welcome. I'm really looking forward to it. IRV LUSTIG: All right. So tell me, when did you first learn about operations research? GEORGE NEMHAUSER: So basically, I am a chemical engineer. And I think it was the summer between when I graduated with a Bachelor's degree in Chemical Engineering and the fall, when I was going to go off to graduate school at Northwestern for Chemical Engineering, I had a job with the research department of Allied Chemical. And there was a guy-- I think he was my supervisor who was working there-- who told me he was taking a part-time degree at Princeton and he was studying things like linear programming and game theory and I think maybe Kuhn, Tucker conditions, And he told me about this kind of stuff and I thought, wow, this is really interesting stuff, much more interesting than what I'm doing in chemical engineering. So when I got to Northwestern, as a first-year graduate student in Chemical Engineering, I had one elective course. And I looked and there was this new course called Operations Research and it included linear programming and game theory and stuff like that. I said, that's it. -
Computational Optimization and Applications
Computational Optimization and Applications A Review on the Performance of Linear and Mixed Integer Two-Stage Stochastic Programming Algorithms and Software --Manuscript Draft-- Manuscript Number: Full Title: A Review on the Performance of Linear and Mixed Integer Two-Stage Stochastic Programming Algorithms and Software Article Type: Manuscript Keywords: Stochastic programming; L-shaped method; Scenario Decomposition; Software benchmark Corresponding Author: I. Grossmann Carnegie-Mellon University Pittsburgh,, PA UNITED STATES Corresponding Author Secondary Information: Corresponding Author's Institution: Carnegie-Mellon University Corresponding Author's Secondary Institution: First Author: Juan J Torres First Author Secondary Information: Order of Authors: Juan J Torres Can Li Robert M Apap I. Grossmann Order of Authors Secondary Information: Funding Information: Powered by Editorial Manager® and ProduXion Manager® from Aries Systems Corporation Manuscript Click here to access/download;Manuscript;TwoStage.pdf Click here to view linked References Noname manuscript No. (will be inserted by the editor) 1 2 3 4 5 A Review on the Performance of Linear and 6 Mixed Integer Two-Stage Stochastic Programming 7 Algorithms and Software 8 9 10 Juan J. Torres · Can Li · Robert M. 11 Apap · Ignacio E. Grossmann 12 13 14 15 16 Received: date / Accepted: date 17 18 19 Abstract This paper presents a tutorial on the state-of-the-art methodologies 20 for the solution of two-stage (mixed-integer) linear stochastic programs and 21 provides a list of software designed for this purpose. The methodologies are 22 classified according to the decomposition alternatives and the types of the vari- 23 ables in the problem. We review the fundamentals of Benders Decomposition, 24 Dual Decomposition and Progressive Hedging, as well as possible improve- 25 26 ments and variants. -
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.