Search Results - 90C06 Large-scale problems in mathematical programming

Complementary composite minimization, small gradients in general norms, and applications by Diakonikolas, Jelena, Guzmán, Cristóbal

“…Composite minimization is a powerful framework in large-scale convex optimization, based on decoupling of the objective function into terms with structurally different properties and allowing…”
Get full text

A new computational framework for log-concave density estimation by Chen, Wenyu, Mazumder, Rahul, Samworth, Richard J.

“…In statistics, log-concave density estimation is a central problem within the field of nonparametric inference under shape constraints…”
Get full text

A MIP framework for non-convex uniform price day-ahead electricity auctions by Madani, Mehdi, Van Vyve, Mathieu

“…It is well known that a market equilibrium with uniform prices often does not exist in non-convex day-ahead electricity auctions. We consider the case of the…”
Get full text

Randomized first order algorithms with applications to ℓ 1-minimization by Juditsky, Anatoli, Kılınç Karzan, Fatma, Nemirovski, Arkadi

Get full text

An efficient Hessian based algorithm for solving large-scale sparse group Lasso problems by Zhang, Yangjing, Zhang, Ning, Sun, Defeng, Toh, Kim-Chuan

“… In this paper, we develop an efficient augmented Lagrangian method for large-scale non-overlapping sparse group Lasso problems with each subproblem being solved by a superlinearly convergent inexact…”
Get full text

Large-scale Unit Commitment under uncertainty by Tahanan, Milad, van Ackooij, Wim, Frangioni, Antonio, Lacalandra, Fabrizio

“… It has always been a large-scale, non-convex difficult problem, especially in view of the fact that operational requirements imply that it has to be solved in an unreasonably small time for its size…”
Get full text

A cutting-plane approach for large-scale capacitated multi-period facility location using a specialized interior-point method by Castro, Jordi, Nasini, Stefano, Saldanha-da-Gama, Francisco

“…We propose a cutting-plane approach (namely, Benders decomposition) for a class of capacitated multi-period facility location problems…”
Get full text

Solving Large-Scale Least Squares Semidefinite Programming by Alternating Direction Methods by He, Bingsheng, Xu, Minghua, Yuan, Xiaoming

“…The well-known least squares semidefinite programming (LSSDP) problem seeks the nearest adjustment of a given symmetric matrix in the intersection of the cone…”
Get full text

An adaptive augmented Lagrangian method for large-scale constrained optimization by Curtis, Frank E., Jiang, Hao, Robinson, Daniel P.

“…We propose an augmented Lagrangian algorithm for solving large-scale constrained optimization problems…”
Get full text

A parallelizable augmented Lagrangian method applied to large-scale non-convex-constrained optimization problems by Boland, Natashia, Christiansen, Jeffrey, Dandurand, Brian, Eberhard, Andrew, Oliveira, Fabricio

“…We contribute improvements to a Lagrangian dual solution approach applied to large-scale optimization problems whose objective functions are convex, continuously differentiable and possibly nonlinear…”
Get full text

Sublinear time algorithms for approximate semidefinite programming by Garber, Dan, Hazan, Elad

“… We present an approximation algorithm for this problem that runs in sublinear time in the size of the data…”
Get full text

A proximal trust-region method for nonsmooth optimization with inexact function and gradient evaluations by Baraldi, Robert J., Kouri, Drew P.

“…Many applications require minimizing the sum of smooth and nonsmooth functions. For example, basis pursuit denoising problems in data science require minimizing a measure of data misfit plus an ℓ 1 -regularizer…”
Get full text

On parallelization of a stochastic dynamic programming algorithm for solving large-scale mixed 0–1 problems under uncertainty by Aldasoro, Unai, Escudero, Laureano F., Merino, María, Monge, Juan F., Pérez, Gloria

“…A parallel computing implementation of a Serial Stochastic Dynamic Programming approach referred to as the S-SDP algorithm is introduced to solve large-scale multiperiod mixed 0…”
Get full text

Parallel Algorithms for Large-scale Linearly Constrained Minimization Problem by Han, Cong-ying, Zheng, Fang-ying, Guo, Tian-de, He, Guo-ping

“… amount each iteration and is closer to practical applications for solve large-scale nonlinear programming…”
Get full text

Quadratic regularizations in an interior-point method for primal block-angular problems by Castro, Jordi, Cuesta, Jordi

“…One of the most efficient interior-point methods for some classes of primal block-angular problems solves the normal equations by a combination of Cholesky factorizations and preconditioned conjugate…”
Get full text

Computational bounds for elevator control policies by large scale linear programming by Heinz, Stefan, Rambau, Jörg, Tuchscherer, Andreas

“…We computationally assess policies for the elevator control problem by a new column-generation approach for the linear programming method for discounted infinite-horizon Markov decision problems…”
Get full text

Primal-Dual Active-Set Methods for Large-Scale Optimization by Robinson, Daniel P.

“…In this paper, we introduce two primal-dual active-set methods for solving large-scale constrained optimization problems…”
Get full text

Large-scale optimization with the primal-dual column generation method by Gondzio, Jacek, González-Brevis, Pablo, Munari, Pedro

“…The primal-dual column generation method (PDCGM) is a general-purpose column generation technique that relies on the primal-dual interior point method to solve the restricted master problems…”
Get full text

Dynamic graph generation for the shortest path problem in time expanded networks by Fischer, Frank, Helmberg, Christoph

“…In discrete optimization problems the progress of objects over time is frequently modeled by shortest path problems in time expanded networks, but longer time spans or finer time discretizations…”
Get full text

Lower complexity bounds of first-order methods for convex-concave bilinear saddle-point problems by Ouyang, Yuyuan, Xu, Yangyang

“… In this paper, we pursue the opposite direction by deriving lower complexity bounds of first-order methods on large-scale SPPs…”
Get full text