COAP Best Paper Awards

• Jeff Linderoth and Stephen Wright,
  Decomposition Algorithms for Stochastic Programming on a Computational Grid,
  COAP, 24 (2003), pp. 207-250.
• Luca Bergamaschi, Jacek Gondzio, and Giovanni Zilli,
  Preconditioning Indefinite Systems in Interior Point Methods for Optimization,
  COAP, 28 (2004), pp. 149-171.
• Julian Hall and Ken McKinnon,
  Hyper-sparsity in the Revised Simplex Method and How to Exploit It,
  COAP, 32 (2005), pp. 259-283.
• Walter Murray and Uday Shanbhag,
  A Local Relaxation Approach for the Siting of Electrical Substations,
  COAP, 33 (2006), pp. 7-49.
• Olvi Mangasarian,
  Absolute Value Programming,
  COAP, 36 (2007), pp. 43-53.
• P.M. Hahn, B.-J. Kim, M. Guignard, J.M. Smith and Y.-R. Zhu,
  An algorithm for the generalized quadratic assignment problem,
  COAP, 40 (2008), pp. 351-372.
• M. Weiser, T. Gänzler, and A. Schiela,
  A control reduced primal interior point method for a
  class of control constrained optimal control problems,
  COAP, 41 (2008), pp. 127-145.
• Samuel Burer and Dieter Vandenbussche,
  Globally solving box-constrained nonconvex quadratic
  programs with semidefinite-based finite branch-and-bound,
  COAP, 43 (2009), pp. 181-195.
• Marco D’Apuzzo, Valentina De Simone and Daniela di Serafino,
  On mutual impact of numerical linear algebra and large-scale
  optimization with focus on interior point methods,
  COAP, 45 (2010), pp. 283-310.
• Ian Kopacka and Michael Hintermüller,
  A smooth penalty approach and a nonlinear multigrid algorithm for elliptic MPECs,
  COAP, 50 (2011), pp. 111-145.
• Chungen Shen, Sven Leyffer, and Roger Fletcher,
  A nonmonotone filter method for nonlinear optimization,
  COAP, 52 (2012), pp. 583-607.
• Miles Lubin, J.A. Julian Hall, Cosmin G. Petra, and Mihai Anitescu,
  Parallel distributed-memory simplex for large-scale stochastic LP problems,
  COAP, 55 (2013), pp. 571-596.
• Daniel Espinoza and Eduardo Moreno,
  A primal-dual aggregation algorithm for minimizing conditional value-at-risk in linear programs,
  COAP, 59 (2014), pp. 617-638.
• Qi Huangfu and Julian Hall,
  Novel update techniques for the revised simplex method,
  COAP, 60 (2015), pp. 587-608.
• Pietro Belotti, Pierre Bonami, Matteo Fischetti, Andrea Lodi, Michele Monaci, Amaya Nogales-Gómez, and Domenico Salvagnin,
  On handling indicator constraints in mixed integer programming,
  COAP, 65 (2016), pp. 545-566.
• Sergio González-Andrade,
  A preconditioned descent algorithm for variational inequalities of the second kind involving the p-Laplacian operator,
  COAP, 66 (2017), pp. 123-162.
• Christoph Buchheim, Renke Kuhlmann, and Christian Meyer,
  Combinatorial optimal control of semilinear elliptic PDEs,
  COAP, 70 (2018), pp. 641-675.
• S. Gratton, C. W. Royer, L. N. Vicente, and Z. Zhang,
  Direct search based on probabilistic feasible descent for bound and linearly constrained problems,
  COAP, 72 (2019), pp. 525-559.
• Andreas M. Tillmann,
  Computing the spark: mixed-integer programming for the (vector) matroid girth problem,
  COAP, 74 (2019), pp. 387-441.
• Nicolas Loizou and Peter Richtarik,
  Momentum and stochastic momentum for stochastic gradient, Newton, proximal point and subspace descent methods,
  COAP, 77 (2020), pp. 653-710.
• Christian Kanzow and Theresa Lechner, Globalized inexact proximal Newton-type methods for nonconvex composite functions,  COAP, 78 ( 2021), pp. 377-410.
• Alberto De Marchi,  On a primal‑dual Newton proximal method for convex quadratic programs, COAP,  81 ( 2022), pp. 369-395.
• Matteo Lapucci and Pierluigi Mansueto, A limited memory Quasi-Newton approach for multi-objective optimization, 85 (2023), pp. 33-73.
• Marco Loccatelli, A new technique to derive tight convex underestimators
  (sometimes envelopes), 87 (2024), pp. 475-499.
• Youssef Diouane, Vyacheslav Kungurtsev, Francesco Rinaldi, and
  Damiano Zeffiro, Inexact direct-search methods for bilevel optimization problems, 88 (2024), pp. 469-490.