Computational Optimization and Applications - COAP Best Paper Award
Each year the Editorial Board of Computational Optimization and Applications (COAP) selects a paper from the preceding year’s publications for the Best Paper Award. Below are the names of the recipients of the Best Paper Award:
Jeff Linderoth and Stephen Wright (this opens in a new tab),
Decomposition Algorithms for Stochastic Programming on a Computational Grid,
COAP, 24 (2003), pp. 207-250.
Luca Bergamaschi, Jacek Gondzio, and Giovanni Zilli (this opens in a new tab),
Preconditioning Indefinite Systems in Interior Point Methods for Optimization,
COAP, 28 (2004), pp. 149-171.
Julian Hall and Ken McKinnon (this opens in a new tab),
Hyper-sparsity in the Revised Simplex Method and How to Exploit It,
COAP, 32 (2005), pp. 259-283.
Walter Murray and Uday Shanbhag (this opens in a new tab),
A Local Relaxation Approach for the Siting of Electrical Substations,
COAP, 33 (2006), pp. 7-49.
Olvi Mangasarian (this opens in a new tab),
Absolute Value Programming,
COAP, 36 (2007), pp. 43-53.
P.M. Hahn, B.-J. Kim, M. Guignard, J.M. Smith and Y.-R. Zhu (this opens in a new tab),
An algorithm for the generalized quadratic assignment problem,
COAP, 40 (2008), pp. 351-372.
M. Weiser, T. Gänzler, and A. Schiela (this opens in a new tab),
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 (this opens in a new tab),
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 (this opens in a new tab),
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 (this opens in a new tab),
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 (this opens in a new tab),
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 (this opens in a new tab),
Parallel distributed-memory simplex for large-scale stochastic LP problems,
COAP, 55 (2013), pp. 571-596.
Daniel Espinoza and Eduardo Moreno (this opens in a new tab),
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 (this opens in a new tab),
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 (this opens in a new tab),
On handling indicator constraints in mixed integer programming
COAP, 65 (2016), pp. 545-566.
Sergio González-Andrade (this opens in a new tab),
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 (this opens in a new tab),
Combinatorial optimal control of semilinear elliptic PDEs
COAP, 70 (2018), pp. 641-675.
Serge Gratton, Clément W. Royer, Luis Nunes Vicente, and Zaikun Zhang (this opens in a new tab),
Direct search based on probabilistic feasible descent for bound and linearly constrained problems
COAP, 72 (2019), pp. 525–559.
Andreas Tillmann (this opens in a new tab),
Computing the spark: mixed-integer programming for the (vector) matroid girth problem
COAP, 74 (2019), pp. 387–441.
Nicolas Loizou & Peter Richtárik (this opens in a new tab)
Momentum and stochastic momentum for stochastic gradient, Newton, proximal point and subspace descent methods
COAP, 77 (2020), pp. 653–710.
Christian Kanzow & Theresa Lechner (this opens in a new tab)
Globalized inexact proximal Newton-type methods for nonconvex composite functions
COAP, 78 (2021), pp. 377–410.
Alberto De Marchi (this opens in a new tab)
On a primal-dual Newton proximal method for convex quadratic programs
COAP, 81 (2022), pp. 369–395.