Pioneers and Innovators (International Series in Operations
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The Artificial Cold War Content of Game Theory and Operations Research Richard Vahrenkamp [University of Kassel, Germany]
real-world economics review, issue no. 88 subscribe for free Nominal science without data – the artificial Cold War content of Game Theory and Operations Research Richard Vahrenkamp [University of Kassel, Germany] Copyright: Richard Vahrenkamp 2019 You may post comments on this paper at https://rwer.wordpress.com/comments-on-rwer-issue-no-88/ Abstract Expanding upon literature on early digital computers, this paper shows the role mathematicians have undertaken in founding the academic fields of Game Theory and Operations Research, and details how they were supported by the mathematics departments of military agencies in branches of the US Armed Services. This paper claims that application is only decoration. Other than astronomy, physics and engineering, where experiments generate data analysed with the aid of models and appropriate software on computers, Game Theory and Operations Research are not data driven but method driven and remain a branch of applied mathematics. They use the method of “abstractification” in economy and society to derive their models but lack a layer of empirical research needed to generate data and to apply their methods in economics and society. Therefore, their models were only nominal mathematics without application. Introduction Since 1945, the United States had experienced a unique innovation push with the computer, the nuclear weapon, new air combat weapons and the transistor within just a few years. These innovations were accompanied by Game Theory and Operations Research in the academic field. Widely–held is the view that computers supplemented the mathematical concepts of Game Theory and Operations Research and gave these fields a fresh impulse. Together, they established the view of the world as a space of numbers and introduced quantitative methods in economics, political science and in sociology. -
Strength in Numbers: the Rising of Academic Statistics Departments In
Agresti · Meng Agresti Eds. Alan Agresti · Xiao-Li Meng Editors Strength in Numbers: The Rising of Academic Statistics DepartmentsStatistics in the U.S. Rising of Academic The in Numbers: Strength Statistics Departments in the U.S. Strength in Numbers: The Rising of Academic Statistics Departments in the U.S. Alan Agresti • Xiao-Li Meng Editors Strength in Numbers: The Rising of Academic Statistics Departments in the U.S. 123 Editors Alan Agresti Xiao-Li Meng Department of Statistics Department of Statistics University of Florida Harvard University Gainesville, FL Cambridge, MA USA USA ISBN 978-1-4614-3648-5 ISBN 978-1-4614-3649-2 (eBook) DOI 10.1007/978-1-4614-3649-2 Springer New York Heidelberg Dordrecht London Library of Congress Control Number: 2012942702 Ó Springer Science+Business Media New York 2013 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. Exempted from this legal reservation are brief excerpts in connection with reviews or scholarly analysis or material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Duplication of this publication or parts thereof is permitted only under the provisions of the Copyright Law of the Publisher’s location, in its current version, and permission for use must always be obtained from Springer. -
Curriculum Vitæ
Aleksandr M. Kazachkov May 30, 2021 Contact Department of Industrial and Systems Engineering Website akazachk.github.io Information Herbert Wertheim College of Engineering Email akazachkov@ufl.edu 303 Weil Hall, P.O. Box 116595 Office 401B Weil Hall Gainesville, FL 32611-6595, USA Phone +1.352.273.4902 Research Discrete optimization, including theoretical, methodological, and applied aspects, with an emphasis on devel- Interests oping better cutting plane techniques and open-source computational contributions Computational economics, particularly on the fair allocation of indivisible resources and fair mechanism design Social good applications, such as humanitarian logistics and donation distribution Academic University of Florida, Department of Industrial and Systems Engineering, Gainesville, FL, USA Positions Assistant Professor January 2021 – Present Courtesy Assistant Professor March 2020 – December 2020 Polytechnique Montréal, Department of Mathematics and Industrial Engineering, Montréal, QC, Canada Postdoctoral Researcher under Andrea Lodi May 2018 – December 2020 Education Carnegie Mellon University, Tepper School of Business, Pittsburgh, PA, USA Ph.D. in Algorithms, Combinatorics, and Optimization under Egon Balas May 2018 Dissertation: Non-Recursive Cut Generation M.S. in Algorithms, Combinatorics, and Optimization May 2013 Cornell University, College of Engineering, Ithaca, NY, USA B.S. in Operations Research and Engineering with Honors, Magna Cum Laude May 2011 Publications [1] P.I. Frazier and A.M. Kazachkov. “Guessing Preferences: A New Approach to Multi-Attribute Ranking and Selection”, Winter Simulation Conference, 2011. [2] J. Karp, A.M. Kazachkov, and A.D. Procaccia. “Envy-Free Division of Sellable Goods”, AAAI Conference on Artificial Intelligence, 2014. [3] J.P. Dickerson, A.M. Kazachkov, A.D. Procaccia, and T. -
Koopmans in the Soviet Union
Koopmans in the Soviet Union A travel report of the summer of 1965 Till Düppe1 December 2013 Abstract: Travelling is one of the oldest forms of knowledge production combining both discovery and contemplation. Tjalling C. Koopmans, research director of the Cowles Foundation of Research in Economics, the leading U.S. center for mathematical economics, was the first U.S. economist after World War II who, in the summer of 1965, travelled to the Soviet Union for an official visit of the Central Economics and Mathematics Institute of the Soviet Academy of Sciences. Koopmans left with the hope to learn from the experiences of Soviet economists in applying linear programming to economic planning. Would his own theories, as discovered independently by Leonid V. Kantorovich, help increasing allocative efficiency in a socialist economy? Koopmans even might have envisioned a research community across the iron curtain. Yet he came home with the discovery that learning about Soviet mathematical economists might be more interesting than learning from them. On top of that, he found the Soviet scene trapped in the same deplorable situation he knew all too well from home: that mathematicians are the better economists. Key-Words: mathematical economics, linear programming, Soviet economic planning, Cold War, Central Economics and Mathematics Institute, Tjalling C. Koopmans, Leonid V. Kantorovich. Word-Count: 11.000 1 Assistant Professor, Department of economics, Université du Québec à Montréal, Pavillon des Sciences de la gestion, 315, Rue Sainte-Catherine Est, Montréal (Québec), H2X 3X2, Canada, e-mail: [email protected]. A former version has been presented at the conference “Social and human sciences on both sides of the ‘iron curtain’”, October 17-19, 2013, in Moscow. -
Data Envelopment
Emrouznejad, A., R. Banker, L. Neralić (2019). Advances in Data Envelopment Analysis: Celebrating the 40th anniversary of DEA and the 100th anniversary of Professor Abraham Charnes’ birthday, European Journal of Operational Research, in Press, https://doi.org/10.1016/j.ejor.2019.02.020 Advances in Data Envelopment Analysis Celebrating the 40th anniversary of DEA and the 100th anniversary of Professor Abraham Charnes’ birthday Ali Emrouznejad1*, Rajiv Banker2, Luka Neralić3 1 Aston Business School, Aston University, Birmingham, UK 2 Fox School of Business and Management, Temple University, Philadelphia, PA 19122, United States 3 University of Zagreb, Faculty of Economics and Business, Zagreb, Croatia Abraham Charnes was born in Hopewell, Virginia, USA on September 4, 1917, son of Harry and Rebecca Charnes. He died on December 19, 1992 in Austin, Texas at the age of 75. Dr. Charnes graduated in mathematics from the University of Illinois (Urbana-Champaign) in 1938, where he also received a master's degree in mathematics in 1939. After that he received a graduate scholarship to study at Harvard, but this was interrupted by World War II. In 1942 he entered the U. S. Naval Reserve as an Ensign OV(S) and worked in electromagnetics, torpedo performance and control, supersonic flight, fire control, weapon damage assessment and did the first U. S. pro-submarine operations research. He returned to the University of Illinois where he received a PhD degree in 1947. His dissertation was entitled “Wing-Body Interaction in Linear Supersonic Flow” (adviser D. G. Bourgin). In 1948/49 he began his post-doctoral academic career as an Assistant Professor of Mathematics at Carnegie Institute of Technology. -
The Management of Information & Knowledge; Meeting of the Panel on Science and Technology With
DOCUMENT RESUME ED 040 730 LI 002 050 TITLE The Management of Information & Knowledge; Meeting of the Panel on Science and Technology with the Committee on Science and Astronautics, U.S. House of Representatives. INSTITUTION Congress of the U.S., Washington, D.C. House Committee on Science and Astronautics. PUB DATE 70 NOTE 243p.; Proceedings of the 11th meeting, 91st Congress, 2nd session, January 27-29, 1970 EDRS PRICE EDRS Price MF-$1.00 HC-$12.25 DESCRIPTORS *Committees, *Communications, *Computers, *Economics, *Information Processing, Information Systems ABSTRACT The emphasis of the eleventh meeting of the Panelon Science and Technology was on the management of information and knowledge. It was organized essentially as a seminar with twopapers given at each session. The topic of the first twopapers presented was: "Computers, Communications, and the Economy." The papers given at the second session were concerned with the kinds of ideals which have been guiding this society and the adequacy of these ideals. The next two papers covered education in a changing world. The problems of privacy and technological obsolescenceswere covered by another speaker. These papers are interspersed by introductory keynote speeches and discussion, sessions. The appendix contains biographies of the panel participants. (NH) PA$EL, ON SCIENCE AND TgqiNotocy, ' IILEyENTLMMING-' , MANAGEMENT OF INFORMATION & KNOWLEDGE ti, OCEEDING-S, . r;BEFOitE IiiMITTEE JON I AND 18TRONAUTIC$ 1101iSE OF jr,REEIES8NTATIVES' NTETY-FIRST CONGRES 1",SecoNp sESSiopi , e 1 JANUARY 27 '28; AND /29,, 1070i; 1 '1 ./3 [No.' .1 Printed for he use of the Committee\,) au Seienee_ aoa A,stronauttea -1, e. 't, L I . -
2019 Contents 2019
mathematical sciences news 2019 contents 2019 Editor-in-Chief Tom Bohman Contributing Writers Letter from Department 03 Tom Bohman Head, Tom Bohman Jocelyn Duffy Bruce Gerson Florian Frick 04 Ben Panko Emily Payne Faculty Notes Ann Lyon Ritchie Franziska Weber Graphic Design and Photography 10 Carnegie Mellon University Expanding the Boundaries on Marketing & Communications Summer Undergraduate Research Mellon College of Science Communications 14 Carnegie Mellon University Frick's Fellowship Department of Mathematical Sciences Wean Hall 6113 Pittsburgh, PA 15213 20 cmu.edu/math In Memorium Carnegie Mellon University does not discriminate in admission, employment, or administration of its programs or activities on the basis of race, color, national origin, sex, 24 handicap or disability, age, sexual orientation, gender identity, religion, creed, ancestry, belief, veteran status, or genetic information. Furthermore, Carnegie Mellon University does Alumni News not discriminate and is required not to discriminate in violation of federal, state, or local laws or executive orders. Inquiries concerning the application of and compliance with this statement should be directed to the university ombudsman, Carnegie Mellon University, 5000 Forbes 26 Avenue, Pittsburgh, PA 15213, telephone 412-268-1018. Obtain general information about Carnegie Mellon University Student News by calling 412-268-2000. Produced for the Department of Mathematical Sciences by Marketing & Communications, November, 2019, 20-137. ©2019 Carnegie Mellon University, All rights reserved. No 30 part of this publication may be reproduced in any form without written permission from Carnegie Mellon University's Department of Mathematical Sciences. Class of 2019 1 Letter from Mathematics Department Head, Tom Bohman Undergraduate research has become a hallmark of a Carnegie Mellon University education, with students citing that it has helped to prepare them for their futures in academia and the workforce. -
On the Depth of Cutting Planes
On the depth of cutting planes Laurent Poirrier, James Yu∗ flpoirrier,[email protected] March 12, 2019 Abstract We introduce a natural notion of depth that applies to individual cutting planes as well as entire families. This depth has nice properties that make it easy to work with theoretically, and we argue that it is a good proxy for the practical strength of cutting planes. In particular, we show that its value lies in a well-defined interval, and we give parametric upper bounds on the depth of two prominent types of cutting planes: split cuts and intersection cuts from a simplex tableau. Interestingly, these parametric bounds can help explain behaviors that have been observed computationally. For polyhedra, the depth of an individual cutting plane can be computed in polynomial time through an LP formulation, and we show that it can be computed in closed form in the case of corner polyhedra. 1 Introduction Cutting planes (also called valid inequalities or cuts) have proven computationally useful since the very early history of Integer Programming (IP). In the pioneering work of Dantzig, Fulkerson and Johnson [10] on the traveling salesman problem, cutting planes were the main computational tool alongside the simplex method. They were initially less successful for general IP problems, where they were largely outperformed by Land and Doig's branch-and-bound method [23]. However, in the mid-nineties, Balas, Ceria and Cornu´ejols[2] proposed combining the two: first adding a few rounds of cuts, before resorting to branch-and-bound. Since then, cutting planes have become a central component of IP solvers [3], the most effective single families of cuts being Gomory's Mixed-Integer (GMI) cuts [19], and Nemhauser and Wolsey's Mixed-Integer Rounding (MIR) cuts [24, 25]. -
Reputation and Equilibrium Characterization in Repeated Games with Conflicting Interests
ECONOMETRICA JOURNAL OF THE ECONOMETRIC SOCIETY An International Society for the Advancement of Economic Theory in its Relation to Statistics and Mathematics VOLUME 61 <41510156620013 <41510156620013 8 Z 91-80(61,1 1993 Un ivarsflots- I lek München INDEX ARTICLES AASNESS, JORGEN, ERIK BI0RN, AND TERJE SKJERPEN: Engel Functions, Panel Data, and Latent Variables 1395 ANDREWS, DONALD W. K.: Exactly Median-Unbiased Estimation of First Order Auto- regressive/Unit Root Models 139 : Tests for Parameter Instability and Structural Change with Unknown Change Point. 821 BEAUDRY, PAUL, AND MICHEL POITEVIN: Signalling and Renegotiation in Contractual Relationships 745 BENOÎT, JEAN-PIERRE, AND VIJAY KRISHNA: Renegotiation in Finitely Repeated Games . 303 BOLLERSLEV, TIM, AND ROBERT F. ENGLE: Common Persistence in Conditional Variances. 167 CALSAMIGLIA, XAVIER, AND ALAN KIRMAN: A Unique Informationally Efficient and Decen• tralized Mechanism with Fair Outcomes 1147 CAMPBELL, DONALD E., AND JERRY S. KELLY: t or 1 — t. That is the Trade-Off 1355 CARLSSON, HANS, AND ERIC VAN DAMME: Global Games and Equilibrium Selection 989 CHANDER, PARKASH: Dynamic Procedures and Incentives in Public Good Economies .... 1341 DROST, FEIKE C, AND THEO E. NIJMAN: Temporal Aggregation of GARCH Processes.... 909 DUFFIE, DARRELL, AND KENNETH J. SINGLETON: Simulated Moments Estimation of Markov Models of Asset Prices 929 ELLISON, GLENN: Learning, Local Interaction, and Coordination 1047 ENGLE, ROBERT F: {See BOLLERSLEV) FAFCHAMPS, MARCEL: Sequential Labor Decisions Under Uncertainty: -
A New Column for Optima Structure Prediction and Global Optimization
76 o N O PTIMA Mathematical Programming Society Newsletter MARCH 2008 Structure Prediction and A new column Global Optimization for Optima by Alberto Caprara Marco Locatelli Andrea Lodi Dip. Informatica, Univ. di Torino (Italy) Katya Scheinberg Fabio Schoen Dip. Sistemi e Informatica, Univ. di Firenze (Italy) This is the first issue of 2008 and it is a very dense one with a Scientific February 26, 2008 contribution on computational biology, some announcements, reports of “Every attempt to employ mathematical methods in the study of chemical conferences and events, the MPS Chairs questions must be considered profoundly irrational and contrary to the spirit in chemistry. If mathematical analysis should ever hold a prominent place Column. Thus, the extra space is limited in chemistry — an aberration which is happily almost impossible — it but we like to use few additional lines would occasion a rapid and widespread degeneration of that science.” for introducing a new feature we are — Auguste Comte particularly happy with. Starting with Cours de philosophie positive issue 76 there will be a Discussion Column whose content is tightly related “It is not yet clear whether optimization is indeed useful for biology — surely biology has been very useful for optimization” to the Scientific contribution, with — Alberto Caprara a purpose of making every issue of private communication Optima recognizable through a special topic. The Discussion Column will take the form of a comment on the Scientific 1 Introduction contribution from some experts in Many new problem domains arose from the study of biological and the field other than the authors or chemical systems and several mathematical programming models an interview/discussion of a couple as well as algorithms have been developed. -
Can Be Formulated As
MIXED INTEGER SECOND ORDER CONE PROGRAMMING SARAH DREWES∗ AND STEFAN ULBRICH † Abstract. This paper deals with solving strategies for mixed integer second order cone problems. We present different lift-and-project based linear and convex quadratic cut generation techniques for mixed 0-1 second-order cone problems and present a new convergent outer approximation based approach to solve mixed integer SOCPs. The latter is an extension of outer approximation based approaches for continuously differ- entiable problems to subdifferentiable second order cone constraint functions. We give numerical results for some application problems, where the cuts are applied in the context of a nonlinear branch-and-cut method and the branch-and-bound based outer approximation algorithm. The different approaches are compared to each other. Key words. Mixed Integer Nonlinear Programming, Second Orde Cone Program- ming, Outer Approximation, Cuts AMS(MOS) subject classifications. 90C11 1. Introduction. Mixed Integer Second Order Cone Programs (MIS- OCP) can be formulated as min cT x s.t. Ax = b x º 0 (1.1) xj ∈ [lj ,uj ] (j ∈ J), xj ∈ Z (j ∈ J), n m,n m n where c ∈ R , A ∈ R , b ∈ R , lj ,uj ∈ R and x º 0 denotes that x ∈ R ki consists of noc part vectors xi ∈ R lying in second order cones defined by T T R Rki−1 Ki = {xi = (xi0,xi1) ∈ × : kxi1k2 ≤ xi0}. Mixed integer second order cone problems have various applications in fi- nance or engineering, for example turbine balancing problems, cardinality- constrained portfolio optimization (cf. Bertsimas and Shioda in [12]) or the problem of finding a minimum length connection network also known as the Euclidian Steiner Tree Problem (ESTP) (cf. -
Disjunctive Programming
Chapter 10 Disjunctive Programming Egon Balas Introduction by Egon Balas In April 1967 I and my family arrived into the US as fresh immigrants from be- hind the Iron Curtain. After a fruitful semester spent with George Dantzig’s group in Stanford, I started working at CMU. My debut in integer programming and entry ticket into Academia was the additive algorithm for 0-1 programming [B65], an im- plicit enumeration procedure based on logical tests akin to what today goes under the name of constraint propagation. As it used only additions and comparisons, it was easy to implement and was highly popular for a while. However, I was aware of its limitations and soon after I joined CMU I started investigating cutting plane procedures, trying to use for this purpose the tools of convex analysis: support func- tions and their level sets, maximal convex extensions, polarity, etc. During the five years starting in 1969, I proposed a number of procedures based on the central idea of intersection cuts [2] (numbered references are to those at the end of the paper, whereas mnemonicized ones are to the ones listed at the end of this introduction): Given any convex set S containing the LP optimum of a mixed integer program (MIP) but containing no feasible integer point in its interior, one can generate a valid cut by intersecting the boundary of S with the extreme rays of the cone defined by the optimal solution to the linear programming relaxation of the MIP and tak- ing the hyperplane defined by the intersection points as the cut.