ASSIGNMENT ALGORITHMS for MULTI-ROBOT TASK ALLOCATION in UNCERTAIN and DYNAMIC ENVIRONMENTS a Dissertation by CHANGJOO NAM Submi

Total Page:16

File Type:pdf, Size:1020Kb

ASSIGNMENT ALGORITHMS for MULTI-ROBOT TASK ALLOCATION in UNCERTAIN and DYNAMIC ENVIRONMENTS a Dissertation by CHANGJOO NAM Submi ASSIGNMENT ALGORITHMS FOR MULTI-ROBOT TASK ALLOCATION IN UNCERTAIN AND DYNAMIC ENVIRONMENTS A Dissertation by CHANGJOO NAM Submitted to the Office of Graduate and Professional Studies of Texas A&M University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Chair of Committee, Dylan A. Shell Committee Members, Sergiy Butenko Yoonsuck Choe Dezhen Song Head of Department, Dilma Da Silva August 2016 Major Subject: Computer Science Copyright 2016 Changjoo Nam ABSTRACT Multi-robot task allocation is a general approach to coordinate a team of robots to complete a set of tasks collectively. The classical works adopt relevant theories from other disciplines (e.g., operations research, economics), but oftentimes they are not adequately rich to deal with the properties from the robotics domain such as perception that is local and communication which is limited. This dissertation reports the efforts on relaxing the assumptions, making problems simpler and developing new methods considering the constraints or uncertainties in robot problems. We aim to solve variants of classical multi-robot task allocation problems where the team of robots operates in dynamic and uncertain environments. In some of these prob- lems, it is adequate to have a precise model of nondeterministic costs (e.g., time, distance) subject to change at run-time. In some other problems, probabilistic or stochastic ap- proaches are adequate to incorporate uncertainties into the problem formulation. For these settings, we propose algorithms that model dynamics owing to robot interactions, new cost representations incorporating uncertainty, algorithms specialized for the representations, and policies for tasks arriving in an online manner. First, we consider multi-robot task assignment problems where costs for performing tasks are interrelated, and the overall team objective need not be a standard sum-of-costs (or utilities) model, enabling straightforward treatment of the additional costs incurred by resource contention. In the model we introduce, a team may choose one of a set of shared resources to perform a task (e.g., several routes to reach a destination), and resource con- tention is modeled when multiple robots use the same resource. We propose efficient task assignment algorithms that model this contention with different forms of domain knowl- edge and compute an optimal assignment under such a model. ii Second, we address the problem of finding the optimal assignment of tasks to a team of robots when the associated costs may vary, which arises when robots deal with uncertain situations. We propose a region-based cost representation incorporating the cost uncer- tainty and modeling interrelationships among costs. We detail how to compute a sensitiv- ity analysis that characterizes how much costs may change before optimality is violated. Using this analysis, robots are able to avoid unnecessary re-assignment computations and reduce global communication when costs change. Third, we consider multi-robot teams operating in probabilistic domains. We represent costs by distributions capturing the uncertainty in the environment. This representation also incorporates inter-robot couplings in planning the team’s coordination. We do not have the assumption that costs are independent, which is frequently used in probabilistic models. We propose algorithms that help in understanding the effects of different char- acterizations of cost distributions such as mean and Conditional Value-at-Risk (CVaR), in which the latter assesses the risk of the outcomes from distributions. Last, we study multi-robot task allocation in a setting where tasks are revealed sequen- tially and where it is possible to execute bundles of tasks. Particularly, we are interested in tasks that have synergies so that the greater the number of tasks executed together, the larger the potential performance gain. We provide an analysis of bundling, giving an un- derstanding of the important bundle size parameter. Based on the qualitative basis, we propose multiple simple bundling policies that determine how many tasks the robots bun- dle for a batched planning and execution. iii ACKNOWLEDGEMENTS The last five years at Texas A&M University were filled with great memories. Studying in a doctoral program, especially out of my homeland, was a big adventure. Although there have been many ups and downs, I am grateful to every moment that brought me to this place. The cover of dissertation shows that I am the sole author, but I would not be able to complete this without the unstinting supports from many teachers, colleagues, friends, and family. I would like to express my sincere gratitude to them. I would like to express my deepest gratitude to my advisor, Dr. Dylan A. Shell. Since our first meeting on a sizzling summer day, he has been an enthusiastic advisor and also a thoughtful mentor. He guided me with his keen insight and exceptional intuition. He did not just try to teach me but threw great questions, which helped me to find the answers by myself. He encouraged me whenever I struggled with my research. Without his support, I would not be where I am today. I am also very grateful for the help and advice from my committee members, Dr. Sergiy Butenko, Dr. Yoonsuck Choe, and Dr. Dezhen Song. Their insightful comments and constructive criticisms on my research made me to follow their high research standard. The current and previous members of Distributed AI Robotics Lab have been great friends and also excellent fellow researchers. I would like to thank Jung-Hwan, Young- Ho, Sasin, Lantao, Plamen, Reza T., Taahir, Ben, Shawn, Yong, Reza O., Yulin, Eric, Kai, and Rui for the discussions, encouragements, and fun times. I am also thankful to the Department of Computer Science and Engineering and its amazing staff. All the administrative work would not be that smooth without the support from the department. The free coffee in the lounge has played a big role for my produc- tivity. The custodial staff has made the building a pleasant place to work in. More im- iv portantly, I appreciate the teaching assistantship opportunities from the department, which gave me valuable experiences in teaching. I am very grateful to Dr. Hyunyoung Lee, who supervised my TA work for several semesters. Her great management skills for the large-sized classes enabled me to carry out my duties without being overloaded. I thank the colleagues at Amazon Robotics, who supported me to finish my internship successfully. I am proud of myself that I had worked with those brilliant people. I have so many fond memories of the summer in Boston. Many friends have helped me stay happy through those difficult years. I will cherish all the unforgettable moments that we had. I would not be able to complete my education without the unbounded love and end- less support from my families in Korea. I deeply appreciate my parents’ dedication and patience. Also, I am thankful to my brother for his efforts on family affairs during my absence. I would like to express my gratitude to my in-laws for having believed and sup- ported me. Most importantly, my wife Eunji has been my ideal companion through the last seven years. The life would not be always happy, but let’s stand by each other whenever and wherever. v TABLE OF CONTENTS Page ABSTRACT . ii ACKNOWLEDGEMENTS . iv TABLE OF CONTENTS . vi LIST OF FIGURES . ix LIST OF TABLES . xv 1. INTRODUCTION . 1 1.1 Motivation . 2 1.2 Research Objective . 5 1.3 Dissertation Contribution . 6 1.4 Organization . 7 2. RELATED WORK AND PRELIMINARIES . 9 2.1 Related Work . 9 2.2 Preliminaries . 11 2.2.1 A mathematical formulation of MRTA . 12 2.2.2 Sensitivity analysis of optimal assignments . 12 3. ASSIGNMENT ALGORITHMS FOR MODELING RESOURCE CONTENTION IN MULTI-ROBOT TASK ALLOCATION . 16 3.1 Related Work . 19 3.2 Problem Formulation . 21 3.2.1 Bipartite multigraph . 21 3.2.2 Multi-choice assignment problem with penalization (mAPwP) . 23 3.2.3 Penalization . 24 3.2.4 Examples . 25 3.3 NP-Hardness of mAPwP Problems . 27 3.3.1 The P-type problem is NP-hard . 27 3.3.2 The L-type problem is in P . 30 3.3.3 The C-type problem is NP-hard . 30 vi 3.3.4 A polynomial-time solvable class of the C-type problem . 31 3.3.5 Remark on the hardness results . 33 3.4 Algorithms for mAP Problems . 34 3.4.1 The multi-choice Hungarian method . 34 3.4.2 The multi-choice Murty’s ranking algorithm . 35 3.4.3 Exact algorithm for the P-type problem . 36 3.4.4 Optimal algorithm for the L-type problem . 38 3.4.5 Approximation algorithm for the C-type problem . 39 3.5 Extension: Modeling Synergies . 41 3.6 Experiments . 43 3.6.1 Penalization functions . 44 3.6.2 Random problem instances . 45 3.6.3 Multi-vehicle transportation problems . 46 3.6.4 Physical robot experiment . 50 3.7 Summary . 52 4. MITIGATING WEAKNESSES IN CENTRALIZED MULTI-ROBOT TASK ALLOCATION WITH UNCERTAIN AND INTERRELATED COSTS . 54 4.1 Related Work . 57 4.2 Interrelated Costs in a Finite Region . 58 4.2.1 The representation . 59 4.2.2 The algorithms mitigating the weaknesses of centralized systems . 61 4.3 Experiments . 73 4.3.1 Computing θ(X∗) .......................... 73 4.3.2 Reducing futile effort . 74 4.3.3 Factorizing a team of robots . 75 4.3.4 Persisting with an initial assignment . 77 4.3.5 Incremental communication . 77 4.3.6 Interrelated costs . 78 4.4 Summary . 80 5. ANALYZING THE SENSITIVITY OF THE OPTIMAL ASSIGNMENT IN PROBABILISTIC MULTI-ROBOT TASK ALLOCATION . 82 5.1 Related Work . 84 5.2 Preliminary: Risk Measures . 85 5.3 The Probabilistic Cost Representation .
Recommended publications
  • What's the Matter with Tie-Breaking? Improving Efficiency in School Choice
    American Economic Review 2008, 98:3, 669–689 http://www.aeaweb.org/articles.php?doi=10.1257/aer.98.3.669 What’s the Matter with Tie-Breaking? Improving Efficiency in School Choice By Aytek Erdil and Haluk Ergin* In several school choice districts in the United States, the student proposing deferred acceptance algorithm is applied after indifferences in priority orders are broken in some exogenous way. Although such a tie-breaking procedure preserves stability, it adversely affects the welfare of the students since it intro- duces artificial stability constraints. Our main finding is a polynomial-time algorithm for the computation of a student-optimal stable matching when pri- orities are weak. The idea behind our construction relies on a new notion which we call a stable improvement cycle. We also investigate the strategic properties of the student-optimal stable mechanism. (JEL C78, D82, I2) Until about a decade ago, children in the United States were assigned to public schools by the district they live in, without taking into account the preferences of their families. Such systems overlooked reallocations of seats which could Pareto improve welfare. Motivated by such con- cerns, several US cities, including New York City, Boston, Cambridge, Charlotte, Columbus, Denver, Minneapolis, Seattle, and St. Petersburg-Tampa, started centralized school choice pro- grams. Typically in these programs, each family submits a preference list of schools, including those outside their district, and then a centralized mechanism assigns students to schools based on the preferences. The mechanisms initially adopted by school choice programs were ad hoc, and did not perform well in terms of efficiency, incentives, and/or stability.
    [Show full text]
  • Ecole Polytechnique Departement D'economie
    ECOLE POLYTECHNIQUE CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE Judge : Don't Vote! Michel BALINSKI Rida LARAKI Novembre 2010 Cahier n° 2010-27 DEPARTEMENT D'ECONOMIE Route de Saclay 91128 PALAISEAU CEDEX (33) 1 69333033 http://www.economie.polytechnique.edu/ / mailto:[email protected] Judge : Don't Vote! 1 Michel Balinski 2 Rida Laraki Novembre 2010 Cahier n° 2010-27 Résumé: Cet article explique pourquoi (1) le modèle traditionnel de choix social n’est pas réaliste, (2) il ne peut en aucun cas proposer une méthode acceptable pour classer et élire, et (3) qu’un modèle plus réaliste implique inévitablement une seule méthode pour classer et élire ---le jugement majoritaire--- qui satisfait le mieux qu’il se peut les critères traditionnels de ce qui constitue une bonne méthode. Abstract: This article explains why (1) the traditional model of the theory of social choice misrepresents reality, (2) it cannot lead to acceptable methods of ranking and electing in any case, and (3) a more realistic model leads inevitably to one method of ranking and electing---majority judgment---that best meets the traditional criteria of what constitutes a good method. Mots clés : Paradoxe d’Arrow, paradoxe de Condorcet, patinage artistique, choix social, jugement majoritaire, manipulation stratégique, vote Key Words : Arrow’s paradox, Condorcet’s paradox, majority judgment, skating, social choice, strategic manipulation, voting Classification JEL: D71, C72 Classification AMS: 91A, 91C, 90B 1 Economics Department of the Ecole Polytechnique and CNRS, France. 2 Economics Department of the Ecole Polytechnique and CNRS, France. Judge : Don’t Vote! Michel Balinski and Rida Laraki The final test of a theory is its capacity to solve the problems which originated it.
    [Show full text]
  • Download File
    Experimental Democracy – Collective Intelligence for a Diverse and Complex World Felix Gerlsbeck Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2013 © 2013 Felix Gerlsbeck All rights reserved Abstract Experimental Democracy – Collective Intelligence for a Diverse and Complex World Felix Gerlsbeck My dissertation is motivated by the following observation: while we care very much about the outcomes of the democratic process, there is widespread uncertainty about ex ante how to produce them—and quite often there is also disagreement and uncertainty about what they are in the first place. Consequently, unless we have a definite idea what “better decision-making” might be, it is not obvious which institutional reforms or changes in democratic structures would actually promote it. Democracy is a wide concept, and not all institutional constellations and rules and regulations that can be called democratic function equally well. In this dissertation therefore I offer a specific model of democracy— “Experimental Democracy”—that unites the view that the quality of decisions matter, with taking into account the circumstances of uncertainty and disagreement that define political problems. On this account, a desirable political mechanism is one that realizes an experimental method of policy-making directed at solving problems, such that we can expect it to make progress over time, even though we cannot rule out that it will get things wrong—possibly even frequently. I also show how democracy may best realize such an experimental method, and which particular institutional features of democracy could serve this purpose.
    [Show full text]
  • Election by Majority Judgement: Experimental Evidence Michel Balinski, Rida Laraki
    Election by Majority Judgement: Experimental Evidence Michel Balinski, Rida Laraki To cite this version: Michel Balinski, Rida Laraki. Election by Majority Judgement: Experimental Evidence. 2007. hal- 00243076 HAL Id: hal-00243076 https://hal.archives-ouvertes.fr/hal-00243076 Preprint submitted on 8 Feb 2008 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. ECOLE POLYTECHNIQUE CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE Election by Majority Judgement: Experimental Evidence Michel Balinski Rida Laraki 17 décembre 2007 Cahier n° 2007-28 LABORATOIRE D'ECONOMETRIE 1rue Descartes F-75005 Paris (33) 1 55558215 http://ceco.polytechnique.fr/ mailto:[email protected] Election by Majority Judgement: Experimental Evidence Michel Balinski1 Rida Laraki2 17 décembre 2007 Cahier n° 2007-28 Résumé: Le jugement majoritaire est une méthode d'élection. Cette méthode est l'aboutissement d'une nouvelle théorie du choix social où les électeurs jugent les candidats au lieu de les ranger. La théorie est développée dans d'autres publications ([2, 4]). Cet article décrit et analyse des expériences électorales conduites pendant les deux dernières élections présidentielles françaises dans plusieurs buts: (1) démontrer que le jugement majoritaire est une méthode pratique, (2) la décrire et établir ses principales propriétés, (3) démontrer qu'elle échappe aux paradoxes classiques, et (4) illustrer comment dans la pratique tous les mécanismes de vote connus violent certains critères importants.
    [Show full text]
  • Beyond the Ballot Box
    BEYOND THE BALLOT BOX Report from the Deepening and Sustaining Democracy in Asia Conference, 11-14 October 2009 The Centre for Bhutan Studies 1 Beyond the Ballot Box Copyright © The Centre for Bhutan Studies 2010 First published: 2010 ISBN 978-99936-14-61-6 The Centre for Bhutan Studies Post Box No. 1111 Thimphu, Bhutan Telephone: 00975-2-321111, 321005 Facsimile: 00975-2- 321001 Email: [email protected] www.bhutanstudies.org.bt www.grossnationalhappiness.com 2 CONTENTS CONTENTS i. Foreword vii ii. Acknowledgements ix iii. Introduction x iv. Opening Remarks Dasho Karma Ura xxi v. Keynote Address Mr Ajay Chhibber 1 vi. Keynote Address HE Jigmi Y Thinley, 10 Prime Minister of Bhutan I. Foundations of Democracy 1. Public Opinion, Happiness, and the Dr Henry S Richardson 25 Will of the People: Policy-making in a Democracy 2. Democracy and Difference: Going Dr Peter Hershock 60 beyond Liberal Freedoms and Illiberal Order 3. Constitutional Values and Rule of Geraldine Fraser- 101 Law Moleketi II. Experiences in Democracy 4. Democracy in the Non-West: Facts, Dr Nitasha Kaul 115 Fictions and Frictions 5. Constitution - the King’s Gift: Dasho Sonam Kinga 134 Defiling and Sanctifying a Sacred Gift 6. Experience of Indian Democracy Pavan K Verma 181 7. Grass Roots Democracy and Dr George Mathew 189 Decentralisation III. Civic Rights and Participation 8. Women’s Role in Politics - Quantity Sultana Kamal 209 and Quality 9. Civil liberties and Security Anthony Grayling 229 10. Citizen’s Assessment of Ahmed Mehboob 237 Parliaments Performance IV. Election and Justice 11. The Majority Judgement: A New Professor Michel 257 Mechanism for Electing and Ranking Balinski 12.
    [Show full text]
  • 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.
    [Show full text]
  • Universität Augsburg
    UNIVERSITÄT AUGSBURG INSTITUT FÜR MATHEMATIK Universitätsstraße 14 D-86135 Augsburg Ehrenpromotion M. Balinski, PhD 7. Juli 2004 by Michel Balinski and Friedrich Pukelsheim Report No. 454 September 2004 Computing electoral districts Michel Balinski CNRS and Ecole Polytechnique 7 July 2004 University of Augsburg Computing Electoral Districts Michel Balinski CNRS and Ecole Polytechnique, Paris Short Abstract Political gerrymandering is the practice of dividing a geographical area into electoral districts, often of highly irregular shape, to favor one political party. New technology has turned the amateurish efforts of the past into precise gerrymandering tools that can seriously subvert an electorate’s intent (and have). This talk will explain why, and how, and what can be done about it. Extended abstract On April 28, 2004 the United States Supreme Court announced its decision in the case of Vieth v. Jubelirer . It refused to declare unconstitutional Pennsylvania’s new map of 19 congressional districts (based on the census of 2000, first used in the 2002 elections). Its bizarrely shaped districts have been compared to animals: the “supine seahorse” and the “upside-down Chinese dragon.” By all accounts Pennsylvania slightly favors the Democratic Party. In the elections of 2000 (when the state had 21 seats) it elected 11 Republicans and 10 Democrats (while giving Gore 50.6% and Bush 46.4% in the state-wide vote); in 2002, with the new map, it elected 12 Republicans and 7 Democrats (while giving a Democratic gubernatorial candidate 55% in the state-wide vote). Five Republican candidates ran unopposed, one Democratic candidate ran unopposed. The map “kidnapped” three Democratic incumbents; it systematically “cracked” Democratic voters among districts; and “packed” and “stacked” them into districts.
    [Show full text]
  • Accomplice Manipulation of the Deferred Acceptance Algorithm
    Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence (IJCAI-21) Accomplice Manipulation of the Deferred Acceptance Algorithm Hadi Hosseini1 , Fatima Umar2 and Rohit Vaish3 1Pennsylvania State University 2Rochester Institute of Technology 3Tata Institute of Fundamental Research [email protected], [email protected], [email protected] Abstract The attractive stability guarantee of the DA algorithm, how- ever, comes at the cost of incentives, as any stable matching The deferred acceptance algorithm is an elegant so- procedure is known to be vulnerable to strategic misreporting lution to the stable matching problem that guar- of preferences [Roth, 1982]. The special proposal-rejection antees optimality and truthfulness for one side of structure of the DA algorithm makes truth-telling a dominant the market. Despite these desirable guarantees, it strategy for the proposing side, i.e., the men [Dubins and is susceptible to strategic misreporting of prefer- Freedman, 1981; Roth, 1982], implying that any strategic be- ences by the agents on the other side. We study havior must occur on the proposed-to side, i.e., the women. a novel model of strategic behavior under the de- This model of strategic behavior by a woman—which we call ferred acceptance algorithm: manipulation through self manipulation—has been the subject of extensive study an accomplice. Here, an agent on the proposed- in economics and computer science [Dubins and Freedman, to side (say, a woman) partners with an agent on 1981; Gale and Sotomayor, 1985b; Demange et al., 1987; the proposing side—an accomplice—to manipulate Teo et al., 2001; Kobayashi and Matsui, 2009; Kobayashi and on her behalf (possibly at the expense of wors- Matsui, 2010; Vaish and Garg, 2017; Deng et al., 2018].
    [Show full text]
  • Michel L. Balinski Books
    MICHEL L. BALINSKI BOOKS 1. Fair Representation : Meeting the Ideal of One Man, One Vote, Yale University Press, New Haven, Ct. and London, 1982 (with H. P. Young). Second edition, Brookings Institution Press, Washington, D.C., 2001. Japanese translation, Chikura-Shobo Publishing Company, Tokyo, 1987. Given the George H. Hallett Award, 2008 (“[For] a book published at least 10 years ago that has made a lasting contribution to … representation and electoral systems.”) 2. Le suffrage universel inachevé, Éditions Belin, Paris, 2004. 3. Majority Judgment: Measuring, Ranking, and Electing, M.I.T. Press, Cambridge, MA, 2011 (with Rida Laraki). BOOKS EDITED 1. Pivoting and Extensions: In Honor of A. W. Tucker, North-Holland Publishing Company, Amsterdam, 1974. 2. Approaches to Integer Programming, North-Holland Publishing Company, Amsterdam, 1975. 3. Nondifferentiable Optimization, North-Holland Publishing Company, Amsterdam, 1975 (with Philip Wolfe). 4. Computational Practice in Mathematical Programming, North-Holland Publishing Company, Amsterdam, 1975 (with Eli Hellerman). 5. Complementarity and Fixed Point Problems, North-Holland Publishing Company, Amsterdam, 1978 (with Richard W. Cottle). 6. Polyhedral Combinatorics : Dedicated to the Memory of D. R. Fulkerson, North-Holland Publishing Company, Amsterdam, 1978 (with Alan J. Hoffman). 7. Mathematical Programming in Use, North-Holland Publishing Company, Amsterdam, 1978 (with Claude Lemarechal). PUBLISHED ARTICLES AND SECLECTED UNPUBLISHED REPORTS 1. “The effect of a traffic light on traffic flow,” Operations Research Report, Massachusetts Institute of Technology, 1955 (with John Hess). 2. “The revised simplex method,” Master of Science Thesis, Massachusetts Institute of Technology, 1956. 3. Navy Supply Systems Research Study (NSSRS), editor, report prepared for the Bureau of Supplies and Accounts, United States Navy, under contract with Mathematica, Inc., 1960.
    [Show full text]
  • Balinski Flyer.Indd
    The MIT Press NEWS MAJORITY JUDG M ENT Measuring, Ranking, and Electing MICHEL BALINSKI AND RIDA LA R AKI In Majority Judgment, Michel Balinski and Rida Laraki argue that the traditional theory of social choice offers no acceptable solution to the problems of how to elect, to judge, or to rank. They find that the traditional model—transforming the “prefer- ence lists” of individuals into a “preference list” of society— is fundamentally flawed in both theory and practice. Balinski and Laraki propose a more realistic model. It leads to an entirely new theory and method—majority judg- ment—proven superior to all known methods. It is at once meaningful, resists strategic manipulation, elicits honesty, and is not subject to the classical paradoxes encountered in practice, notably Condorcet’s and Arrow’s. They offer theoretical, practical, and experimental evidence—from national elections to figure skating competitions—to sup- port their arguments. Drawing on insights from wine, sports, music, and other competitions, Balinski and Laraki argue that the question should not be how to transform many individual rankings into a single collective ranking, but rather, after defining a common language of grades to measure merit, how to transform the many individual evaluations of each com- petitor into a single collective evaluation of all competi- tors. The crux of the matter is a new model in which the traditional paradigm—to compare—is replaced by a new paradigm—to evaluate. Michel Balinski is Directeur de Recherche de classe exceptionnelle (Emeritus), C.N.R.S. and the Laboratoire d’Econométrie, Département d’Économie, École Polytechnique, Palaiseau, France.
    [Show full text]
  • Integer Programming
    50 Years of Integer Programming 1958–2008 Michael Junger¨ · Thomas Liebling · Denis Naddef · George Nemhauser · William Pulleyblank · Gerhard Reinelt · Giovanni Rinaldi · Laurence Wolsey Editors 50 Years of Integer Programming 1958–2008 From the Early Years to the State-of-the-Art 123 Editors Michael Junger¨ Thomas M. Liebling Universitat¨ zu Koln¨ Ecole Polytechnique Fed´ erale´ de Lausanne Institut fur¨ Informatik Faculte´ des Sciences de Base Pohligstraße 1 Institut de Mathematiques´ 50969 Koln¨ Station 8 Germany 1015 Lausanne [email protected] Switzerland Denis Naddef thomas.liebling@epfl.ch Grenoble Institute of Technology - Ensimag George L. Nemhauser Laboratoire G-SCOP Industrial and Systems Engineering 46 avenue Felix´ Viallet Georgia Institute of Technology 38031 Grenoble Cedex 1 Atlanta, GA 30332-0205 France USA [email protected] [email protected] William R. Pulleyblank Gerhard Reinelt IBM Corporation Universitat¨ Heidelberg 294 Route 100 Institut fur¨ Informatik Somers NY 10589 Im Neuenheimer Feld 368 USA 69120 Heidelberg [email protected] Germany Giovanni Rinaldi [email protected] CNR - Istituto di Analisi dei Sistemi Laurence A. Wolsey ed Informatica “Antonio Ruberti” Universite´ Catholique de Louvain Viale Manzoni, 30 Center for Operations Research and 00185 Roma Econometrics (CORE) Italy voie du Roman Pays 34 [email protected] 1348 Louvain-la-Neuve Belgium [email protected] ISBN 978-3-540-68274-5 e-ISBN 978-3-540-68279-0 DOI 10.1007/978-3-540-68279-0 Springer Heidelberg Dordrecht London New York Library of Congress Control Number: 2009938839 Mathematics Subject Classification (2000): 01-02, 01-06, 01-08, 65K05, 65K10, 90-01, 90-02, 90-03, 90-06, 90-08, 90C05, 90C06, 90C08, 90C09, 90C10, 90C11, 90C20, 90C22, 90C27, 90C30, 90C35, 90C46, 90C47, 90C57, 90C59, 90C60, 90C90 c Springer-Verlag Berlin Heidelberg 2010 This work is subject to copyright.
    [Show full text]
  • System and Decision Sciences at Ilasa 1973-1980 Andrzej Wienbicki Peyton Young
    System and Decision Sciences at IlASA 1973-1980 Andrzej Wienbicki Peyton Young INTERNATIONAL IIUSTITUTE FOR APPLIED SYSTEMS ANALYSIS A-2361 LAXEIUBURG, AUSTRIA FOREWORD In October 1981, the International Institute for Applied Systems Analysis (IIASA) marked the ninth anniversary of the signing of its Char- ter, and by the middle of 1981 it had completed its first eight years of research activity. We believe that the time has now come to assess the past achievements of the Institute and to outline future research directions. The successes we have had in the last eight years should be shared with those outside the Insti- tute who are interested in its work - scientists, advisors, and decision makers - people who should also help IIASA shape its future plans. With this aim in mind, Andrzej Wierzbicki and Peyton Young have prepared a report on the activities of the System and Decision Sciences Area (formerly known as the Methodology Project), which reviews past work, discusses current research, and suggests several new directions. We hope that this report will lead to a greater understanding of the work being carried out at IIASA within the System and Decision Sciences Area, and will extend the international network of persons and institutions both collaborating with IIASA and making use of its research. ROGER E. LEVIEN Director International Institute for Applied Systems Analysis ACKIUOWLEDGMENT The authors particularly wish to thank Sheila Auer-Klepp for her pains- taking historical researches on the former staff and publications of the Area and for typing the manuscript. CONTENTS Ovemiew ................................................. 1 BriefHistory .............................................. 2 Current and Future Research Directions ........................
    [Show full text]