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Mathematics | Mathematical Programming Computation - incl. option to publish open access (Editorial Board)

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Mathematical Programming Computation

Mathematical Programming Computation

A Publication of the Mathematical Optimization Society

Editor-in-Chief: Jonathan Eckstein

ISSN: 1867-2949 (print version)
ISSN: 1867-2957 (electronic version)

Journal no. 12532

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Jonathan Eckstein
Business School and Rutgers Center for Operations Research
Rutgers University
100 Rockafeller Road, Livingston Campus
Piscataway, NJ 08854, USA
e-mail: jeckstei@business.rutgers.edu

Production Editor: Wolfgang Dalitz, Konrad-Zuse-Zentrum Berlin, Germany

Area Editors

Alper Atamturk, University of California-Berkeley, CA, USA (Area: Linear and Integer Programming)
Sanjeeb Dash, IBM T.J. Watson Reseach Center, Yorktown Heights, NY USA (Discrete Optimization)
Santanu Dey, Georgia Institute of Technology, Atlanta,GA, USA (Area: Mixed-Integer Nonlinear Programming)
Robert Fourer, Northwestern University, Evanston, IL, USA (Area: Modeling Languages and Systems)
Kim-Chuan Toh, National University of Singapore (Area: Convex Optimization)
Andreas Waechter, Northwestern University, Evanston, IL, USA (Area: Nonlinear Programming)

Associate Editors

Ernesto G. Birgin, University of São Paulo, Brazil
Frank E. Curtis, Lehigh University, Bethlehem, PA, USA
Camil Demetrescu, University of Rome, Italy
Quoc Tran-Dinh, University of North Carolina at Chapel Hill Chapel Hill, NC, USA
Matteo Fischetti, University of Padova, Italy
Emmanuel Fragniere, Haute Ecole de Gestion, Geneva, Switzerland
Philip E. Gill, University of California San Diego, CA, USA
Jacek Gondzio, University of Edinburgh, UK
Simge Küçükyavuz, Northwestern University, Evanston, IL, USA
Xudong Li, Fudan University, Shanghai, China
Xin Liu, Academy of Mathematics and Systems Science, Beijing, China
James Luedtke, University of Wisconsin, Madison, WI, USA
Rafael Marti, University of Valencia, Spain
Alexander Martin, Universität Erlangen-Nürnberg, Germany
Laurent Michel, University of Connecticut, Storrs, CT, USA
Petra Mutzel, Technische Universitaet Dortmund, Germany
Marc Pfetsch, Technische Universitaet Darmstadt, Germany
Hou-Duo Qi, University of Southampton, UK
Nikolaos V. Sahinidis, Carnegie Mellon University, Pittsburg, PA, USA
Melvyn Sim, National University of Singapore
Martin Takáč, Lehigh University, Bethlehem, PA, USA
Huseyin Topaloglu, Cornell University, Ithaca, NY, USA
Michael Ulbrich, Technische Universitaet Muenchen, Germany

Technical Editors

Tobias Achterberg, Gurobi Optimization / Zuse Institute Berlin, Germany
Pietro Belotti, FICO, Birmingham, UK
Hande Y. Benson, Drexel University, Philadelphia, PA, USA
Timo Berthold, FICO, Berlin, Germany 
Andreas Bley, University of Kassel, Germany
Pierre Bonami, IBM Spain, Madrid, Spain
Brian Borchers, New Mexico Tech, Soccoro, NM, USA
Jordi Castro, Universitat Politècnica de Catalunya, Barcelona, Spain
Daniel Espinoza, Universidade de Chile, Santiago, Chile
Armin Fügenschuh, Universität der Bundeswehr, Hamburg, Germany
Ricardo Fukasawa, University of Waterloo, Ontario, Canada
Ambros Gleixner, Konrad-Zuse-Zentrum Berlin, Germany
Andreas Grothey, University of Edinburgh, UK
Julian Hall, University of Edinburgh, UK
William Hart, Sandia National Laboratories, Albuquerque, NM, USA
Benjamin Hiller, Konrad-Zuse-Zentrum Berlin, Germany
Laszlo Ladanyi, IBM ILOG Cplex, Lakeville, CT, USA
Leonardo B. Lopes, University of Arizona, Tucson, AZ, USA
Miles Lubin, Google, New York. NY, USA
Todd S. Munson, Argonne National Laboratory, Lemont, IL, USA
Giacomo Nannicini, IBM T.J. Watson Research Center, Yorktown Heights, NY, USA
Dominique Orban, Ecole Polytechnique de Montréal, Québec, Canada
Nikolaos Ploskas, University of Western Macedonia, Kozani, Greece
Marc Pfetsch, Technische Universität Darmstadt, Germany
Ted Ralphs, Lehigh University, Bethlehem, PA, USA
Domenico Salvagnin, University of Padova, Italy
Lars Schewe, University of Edinburgh, UK
Martin Schmidt, Friedrich-Alexander Universität Erlangen-Nürnberg, Germany
Paulo J.S. Silva, University of Campinas, Brazil 
Dan Steffy, Oakland University, Rochester, MI, USA
Mohit Tawarmalani, Purdue University, West Lafayette, IN, USA
Stefan Vigerske, GAMS, Berlin, Germany
Zaiwen Wen, Pekting University, China
Stefan Wild, Argonne National Laboratory, Lemont, IL,USA
Victor Zavala, University of Wisconsin, Madison, WI, USA

Advisory Board

Robert E. Bixby, Rice University, Houston, TX, USA
Donald Goldfarb, Columbia University, New York, NY, USA
Nick Gould, Rutherford Appleton Laboratory, Oxfordshire, UK
Martin Grötschel, Konrad-Zuse-Zentrum Berlin, Germany
David S. Johnson, Columbia University, New York, NY, USA 
Kurt Mehlhorn, Max-Planck-Institut für Informatik, Saarbrücken, Germany
Hans D. Mittelmann, Arizona State University, Tempe, AZ, USA
Arkadi Nemirovski, Georgia Tech, Atlanta, GA, USA
Jorge Nocedal, Northwestern University, Evanstone, IL, USA
Michael Trick, Carnegie Mellon University, Pittsburgh, PA, USA
Robert Vanderbei, Princeton University, NJ, USA
David P. Williamson, Cornell University, Ithaca, NY, USA

Former Editors-in-Chief:

William J. Cook (2008-2014)
Daniel Bienstock (2014-2018)

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For authors and editors

  • Aims and Scope

    Aims and Scope


    Mathematical Programming Computation (MPC) publishes original research articles advancing the state of the art of practical computation in Mathematical Optimization and closely related fields.  Authors are required to submit software source code and data along with their manuscripts (while open-source software is encouraged, it is not required).  Where applicable, the review process will aim for verification of reported computational results.  Topics of articles include:

    •         New algorithmic techniques, with substantial computational testing

    •         New applications, with substantial computational testing

    •         Innovative software

    •         Comparative tests of algorithms

    •         Modeling environments

    •         Libraries of problem instances

    •         Software frameworks or libraries.

    Among the specific topics covered in MPC are linear programming, convex optimization, nonlinear optimization, stochastic optimization, integer programming, combinatorial optimization, global optimization, network algorithms, and modeling languages.

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