Suchergebnisse - 90C06 Large-scale problems in mathematical programming

Complementary composite minimization, small gradients in general norms, and applications von 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 …”
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A new computational framework for log-concave density estimation von 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 …”
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A MIP framework for non-convex uniform price day-ahead electricity auctions von 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 …”
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Randomized first order algorithms with applications to ℓ 1-minimization von Juditsky, Anatoli, Kılınç Karzan, Fatma, Nemirovski, Arkadi

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An efficient Hessian based algorithm for solving large-scale sparse group Lasso problems von 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 …”
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Large-scale Unit Commitment under uncertainty von 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 …”
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A cutting-plane approach for large-scale capacitated multi-period facility location using a specialized interior-point method von 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 …”
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Solving Large-Scale Least Squares Semidefinite Programming by Alternating Direction Methods von 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 …”
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An adaptive augmented Lagrangian method for large-scale constrained optimization von Curtis, Frank E., Jiang, Hao, Robinson, Daniel P.

“… We propose an augmented Lagrangian algorithm for solving large-scale constrained optimization problems …”
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A parallelizable augmented Lagrangian method applied to large-scale non-convex-constrained optimization problems von 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 …”
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Sublinear time algorithms for approximate semidefinite programming von Garber, Dan, Hazan, Elad

“… We present an approximation algorithm for this problem that runs in sublinear time in the size of the data …”
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A proximal trust-region method for nonsmooth optimization with inexact function and gradient evaluations von 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 …”
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On parallelization of a stochastic dynamic programming algorithm for solving large-scale mixed 0–1 problems under uncertainty von 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 …”
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Parallel Algorithms for Large-scale Linearly Constrained Minimization Problem von 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 …”
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Quadratic regularizations in an interior-point method for primal block-angular problems von 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 …”
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Computational bounds for elevator control policies by large scale linear programming von 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 …”
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Primal-Dual Active-Set Methods for Large-Scale Optimization von Robinson, Daniel P.

“… In this paper, we introduce two primal-dual active-set methods for solving large-scale constrained optimization problems …”
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Large-scale optimization with the primal-dual column generation method von 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 …”
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Dynamic graph generation for the shortest path problem in time expanded networks von 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 …”
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Lower complexity bounds of first-order methods for convex-concave bilinear saddle-point problems von 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 …”
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