Mathematical Programming Computation

Papers
(The TQCC of Mathematical Programming Computation is 5. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-05-01 to 2025-05-01.)
ArticleCitations
Mixed integer bilevel optimization with a k-optimal follower: a hierarchy of bounds205
On technical debt in mathematical programming: An exploratory study138
Learning to use local cuts34
Exact methods for discrete $${\varGamma }$$-robust interdiction problems with an application to the bilevel knapsack problem19
Integer programming column generation: accelerating branch-and-price using a novel pricing scheme for finding high-quality solutions in set covering, packing, and partitioning problems15
An augmented Lagrangian method with constraint generation for shape-constrained convex regression problems15
Optimal patchings for consecutive ones matrices13
Domain-Driven Solver (DDS) Version 2.1: a MATLAB-based software package for convex optimization problems in domain-driven form13
Regularized step directions in nonlinear conjugate gradient methods11
PyEPO: a PyTorch-based end-to-end predict-then-optimize library for linear and integer programming10
Computing minimum-volume enclosing ellipsoids9
LMBOPT: a limited memory method for bound-constrained optimization8
QPALM: a proximal augmented lagrangian method for nonconvex quadratic programs8
Parallel and distributed asynchronous adaptive stochastic gradient methods8
Structure-aware methods for expensive derivative-free nonsmooth composite optimization6
An integrated local-search/set-partitioning refinement heuristic for the Capacitated Vehicle Routing Problem6
Progressively strengthening and tuning MIP solvers for reoptimization6
Correction to: Asynchronous Lagrangian scenario decomposition6
On the generation of metric TSP instances with a large integrality gap by branch-and-cut5
PEPit: computer-assisted worst-case analyses of first-order optimization methods in Python5
Nonlinear conjugate gradient for smooth convex functions5
Adaptive sieving: a dimension reduction technique for sparse optimization problems5
0.62451386451721