Optimization Methods & Software

Papers
(The TQCC of Optimization Methods & Software is 2. 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 2021-07-01 to 2025-07-01.)
ArticleCitations
A majorization penalty method for SVM with sparse constraint36
An adaptive regularization method in Banach spaces35
Sparse convex optimization toolkit: a mixed-integer framework23
Computing subgradients of convex relaxations for solutions of parametric ordinary differential equations23
Discretization and quantification for distributionally robust optimization with decision-dependent ambiguity sets16
Exact gradient methods with memory15
Correction14
The largest- K -norm for general measure spaces and a DC reformulation for L 0 -constrained problems in function sp14
A two-step new modulus-based matrix splitting method for vertical linear complementarity problem13
Practical perspectives on symplectic accelerated optimization12
Numerical simulation of differential-algebraic equations with embedded global optimization criteria10
Spatially sparse optimization problems in fractional order Sobolev spaces10
Data-driven distributionally robust risk parity portfolio optimization9
Toward state estimation by high gain differentiators with automatic differentiation9
Conic optimization-based algorithms for nonnegative matrix factorization8
A hybrid optimal control problem constrained with hyperelasticity and the global injectivity condition7
A mixed-integer programming formulation for optimizing the double row layout problem7
The Dai–Liao-type conjugate gradient methods for solving vector optimization problems6
On the numerical performance of finite-difference-based methods for derivative-free optimization6
Using Nemirovski's Mirror-Prox method as basic procedure in Chubanov's method for solving homogeneous feasibility problems6
Two RMIL-type schemes with compressed sensing applications6
Jordan symmetry reduction for conic optimization over the doubly nonnegative cone: theory and software6
Sequential hierarchical least-squares programming for prioritized non-linear optimal control5
A note on the generalized Hessian of the least squares associated with systems of linear inequalities5
A family of limited memory three term conjugate gradient methods4
The role of local steps in local SGD4
Worst-case evaluation complexity of a quadratic penalty method for nonconvex optimization4
Decentralized gradient tracking with local steps4
AN-SPS: adaptive sample size nonmonotone line search spectral projected subgradient method for convex constrained optimization problems4
An efficient hybrid conjugate gradient method for unconstrained optimization4
Three-operator reflected forward-backward splitting algorithm with double inertial effects3
General framework for binary classification on top samples3
Customized Douglas-Rachford splitting methods for structured inverse variational inequality problems3
Accelerated gradient methods with absolute and relative noise in the gradient3
Towards global parameter estimation exploiting reduced data sets3
Numerical methods for distributed stochastic compositional optimization problems with aggregative structure3
An efficient model for the multiple allocation hub maximal covering problem3
Near-optimal tensor methods for minimizing the gradient norm of convex functions and accelerated primal–dual tensor methods3
Cone-compactness of a set and related topological properties: stability issues and applications3
A meta-heuristic extension of the Lagrangian heuristic framework3
Distributionally robust joint chance-constrained programming with Wasserstein metric3
Two modified conjugate gradient methods for unconstrained optimization3
Inexact tensor methods and their application to stochastic convex optimization3
Preface3
Proximal subgradient method for non-Lipschitz objective functions3
A gradient descent akin method for constrained optimization: algorithms and applications3
On the complexity of a quadratic regularization algorithm for minimizing nonsmooth and nonconvex functions3
Foreword3
Barzilai–Borwein-like rules in proximal gradient schemes for ℓ 1 -regularized problems3
A penalty decomposition approach for multi-objective cardinality-constrained optimization problems2
Reduced basis model predictive control for semilinear parabolic partial differential equations2
Convergences for robust bilevel polynomial programmes with applications2
Superlinear convergence of an interior point algorithm on linear semi-definite feasibility problems2
Approximating Hessian matrices using Bayesian inference: a new approach for quasi-Newton methods in stochastic optimization2
A bundle trust-region algorithm for nonsmooth nonconvex constrained optimization2
An approximate Newton-type proximal method using symmetric rank-one updating formula for minimizing the nonsmooth composite functions2
New iterative algorithms with self-adaptive step size for solving split equality fixed point problem and its applications2
Non-convex regularization and accelerated gradient algorithm for sparse portfolio selection2
Interior point methods for solving Pareto eigenvalue complementarity problems2
A novel approach for solving a class of diffusion identification problems2
Preface2
On minty variational principle for quasidifferentiable vector optimization problems2
Generating linear, semidefinite, and second-order cone optimization problems for numerical experiments2
Bilevel optimization with a multi-objective lower-level problem: risk-neutral and risk-averse formulations2
Stochastic approximation versus sample average approximation for Wasserstein barycenters2
A trust-region scheme for constrained multi-objective optimization problems with superlinear convergence property2
Optimized convergence of stochastic gradient descent by weighted averaging2
An incremental descent method for multi-objective optimization2
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