We use cookies to improve your website experience. To learn about our use of cookies and how you can manage your cookie settings, please see our Cookie Policy. By closing this message, you are consenting to our use of cookies.

Charles Broyden Prize

Optimization Methods and Software

About the prize

The prize was established by the Optimization Methods and Software Editorial Board and Taylor & Francis in 2009. It is awarded annually to the best paper published in the journal from the previous year with a cash prize of £500 and promotion of the winning article, which is made freely available for the following year.

Charles George Broyden received international recognition for his seminal 1965 paper, in which he proposed two methods for solving systems of equations. They later became known as Broyden’s methods. Another of his most important achievements was the derivation of the Broyden-Fletcher-Goldfarb-Shanno (BFGS) updating formula, one of the key tools used in optimization. Moreover, he was among those who derived the symmetric rank-one updating formula, and his name is also attributed to the Broyden family of quasi-Newton methods. Charles G. Broyden died in May 2011 at the age of 78.

The Charles Broyden Prize for the 2018 volume is awarded to:

A framework for solving mixed-integer semidefinite programs

Tristan Gally, Marc E. Pfetsch & Stefan Ulbrich

The prize committee noticed the following:

"Mixed-integer SDPs (MISDPs) arise in many areas of science and engineering. For instance, in wireless communications, many joint selection and resource allocation problems can be tackled via MISDP formulations. Currently, existing MISDP solvers either focus on specific applications (such as max-cut) or rely heavily on reduction to mixed-integer linear or mixed-integer second-order-cone programs. This well written paper takes an important step towards the development of a general-purpose solver for MISDPs. Specifically, it considers a branch-and-bound framework and addresses a number of critical theoretical and practical challenges that arise when solving the sequence of SDPs generated by the branch-and-bound process. Then, it demonstrates the viability of the proposed framework via extensive numerical experiments. It provides an important foundation for further research on general-purpose MISDP solvers."

Optimization Methods and Software

Visit Journal Articles

2018Tristan Gally, Marc E. Pfetsch & Stefan Ulbrich
Tristan Gally, Marc E. Pfetsch & Stefan Ulbrich333
2017Vincent Guigues, Anatoli Juditsky & Arkadi Nemirovski
Non-asymptotic confidence bounds for the optimal value of a stochastic programn325
2016N. Keskar, J. Nocedal, F. Öztoprak and A. Wächter
A second-order method for convex 1-regularized optimization with active-set prediction313
2015Nataša Krejić, Zorana Lužanin, Zoran Ovcin & Irena Stojkovska
Descent direction method with line search for unconstrained optimization in noisy environment306
2014W. de Oliveira & C. Sagastizábal
Level bundle methods for oracles with on-demand accuracy296
2014Y. Shen, Z. Wen & Y. Zhang
Augmented Lagrangian alternating direction method for matrix separation based on low-rank factorization292
2013Andreas Griewank
On stable piecewise linearization and generalized algorithmic differentiation286
2012David A. Fournier, Hans J. Skaug, Johnoel Ancheta, James Ianelli, Arni Magnusson, Mark N. Maunder, Anders Nielsen & John Sibert
AD Model Builder: using automatic differentiation for statistical inference of highly parameterized complex nonlinear models272
2011Didier Henrion & Jérôme Malick
Projection methods for conic feasibility problems: applications to polynomial sum-of-squares decompositions261
2010Felipe Alvarez, Julio López & C. Héctor Ramírez
Interior proximal algorithm with variable metric for second-order cone programming: applications to structural optimization and support vector machines256
2009Giovanni Fasano, José Luis Morales & Jorge Nocedal
On the geometry phase in model-based algorithms for derivative-free optimization241
2008Yu. Nesterov
Rounding of convex sets and efficient gradient methods for linear programming problems231
2008Anna von Heusinger & Christian Kanzow
SC 1 optimization reformulations of the generalized Nash equilibrium problem236

Latest Tweets