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Enhancements of discretization approaches for non-convex mixed-integer quadratically constrained quadratic programming: part II Comput. Optim. Appl. (IF 2.2) Pub Date : 2024-03-18 Benjamin Beach, Robert Burlacu, Andreas Bärmann, Lukas Hager, Robert Hildebrand
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A new proximal heavy ball inexact line-search algorithm Comput. Optim. Appl. (IF 2.2) Pub Date : 2024-03-10 S. Bonettini, M. Prato, S. Rebegoldi
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Local convergence of primal–dual interior point methods for nonlinear semidefinite optimization using the Monteiro–Tsuchiya family of search directions Comput. Optim. Appl. (IF 2.2) Pub Date : 2024-02-28 Takayuki Okuno
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Riemannian preconditioned algorithms for tensor completion via tensor ring decomposition Comput. Optim. Appl. (IF 2.2) Pub Date : 2024-02-27 Bin Gao, Renfeng Peng, Ya-xiang Yuan
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Convergence of successive linear programming algorithms for noisy functions Comput. Optim. Appl. (IF 2.2) Pub Date : 2024-02-26 Christoph Hansknecht, Christian Kirches, Paul Manns
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IPRSDP: a primal-dual interior-point relaxation algorithm for semidefinite programming Comput. Optim. Appl. (IF 2.2) Pub Date : 2024-02-21 Rui-Jin Zhang, Xin-Wei Liu, Yu-Hong Dai
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A projected-search interior-point method for nonlinearly constrained optimization Comput. Optim. Appl. (IF 2.2) Pub Date : 2024-02-21 Philip E. Gill, Minxin Zhang
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An infeasible interior-point arc-search method with Nesterov’s restarting strategy for linear programming problems Comput. Optim. Appl. (IF 2.2) Pub Date : 2024-02-20 Einosuke Iida, Makoto Yamashita
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Convex mixed-integer nonlinear programs derived from generalized disjunctive programming using cones Comput. Optim. Appl. (IF 2.2) Pub Date : 2024-02-20 David E. Bernal Neira, Ignacio E. Grossmann
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An inexact regularized proximal Newton method for nonconvex and nonsmooth optimization Comput. Optim. Appl. (IF 2.2) Pub Date : 2024-02-20 Ruyu Liu, Shaohua Pan, Yuqia Wu, Xiaoqi Yang
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Convex approximations of two-stage risk-averse mixed-integer recourse models Comput. Optim. Appl. (IF 2.2) Pub Date : 2024-02-13 E. Ruben van Beesten, Ward Romeijnders, Kees Jan Roodbergen
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Coordinate descent methods beyond smoothness and separability Comput. Optim. Appl. (IF 2.2) Pub Date : 2024-02-13 Flavia Chorobura, Ion Necoara
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Accelerated forward–backward algorithms for structured monotone inclusions Comput. Optim. Appl. (IF 2.2) Pub Date : 2024-02-11 Paul-Emile Maingé, André Weng-Law
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Efficient gradient-based optimization for reconstructing binary images in applications to electrical impedance tomography Comput. Optim. Appl. (IF 2.2) Pub Date : 2024-02-08
Abstract A novel and highly efficient computational framework for reconstructing binary-type images suitable for models of various complexity seen in diverse biomedical applications is developed and validated. Efficiency in computational speed and accuracy is achieved by combining the advantages of recently developed optimization methods that use sample solutions with customized geometry and multiscale
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A benchmark generator for scenario-based discrete optimization Comput. Optim. Appl. (IF 2.2) Pub Date : 2024-02-06 Matheus Bernardelli de Moraes, Guilherme Palermo Coelho
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A note on the convergence of deterministic gradient sampling in nonsmooth optimization Comput. Optim. Appl. (IF 2.2) Pub Date : 2024-02-06 Bennet Gebken
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Enhancements of discretization approaches for non-convex mixed-integer quadratically constrained quadratic programming: Part I Comput. Optim. Appl. (IF 2.2) Pub Date : 2024-01-30 Benjamin Beach, Robert Burlacu, Andreas Bärmann, Lukas Hager, Robert Hildebrand
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Alternative extension of the Hager–Zhang conjugate gradient method for vector optimization Comput. Optim. Appl. (IF 2.2) Pub Date : 2024-01-24 Qingjie Hu, Liping Zhu, Yu Chen
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A family of Barzilai-Borwein steplengths from the viewpoint of scaled total least squares Comput. Optim. Appl. (IF 2.2) Pub Date : 2024-01-18 Shiru Li, Tao Zhang, Yong Xia
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Internet traffic tensor completion with tensor nuclear norm Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-12-21
Abstract The incomplete data is a common phenomenon in traffic network because of the high measurement cost, the failure of data collection systems and unavoidable transmission loss. Recovering the whole data from incomplete data is a very important task in internet engineering and management. In this paper, we adopt the low-rank tensor completion model equipped with tensor nuclear norm to reconstruct
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A Bregman–Kaczmarz method for nonlinear systems of equations Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-12-07 Robert Gower, Dirk A. Lorenz, Maximilian Winkler
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The continuous stochastic gradient method: part II–application and numerics Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-11-24 Max Grieshammer, Lukas Pflug, Michael Stingl, Andrian Uihlein
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The continuous stochastic gradient method: part I–convergence theory Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-11-23 Max Grieshammer, Lukas Pflug, Michael Stingl, Andrian Uihlein
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Preface to Asen L. Dontchev Memorial Special Issue Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-11-03 William W. Hager, R. Tyrrell Rockafellar, Vladimir M. Veliov
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A fast continuous time approach for non-smooth convex optimization using Tikhonov regularization technique Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-10-25 Mikhail A. Karapetyants
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Optimization over the Pareto front of nonconvex multi-objective optimal control problems Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-10-20 C. Yalçın Kaya, Helmut Maurer
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A new technique to derive tight convex underestimators (sometimes envelopes) Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-10-16 M. Locatelli
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A study of progressive hedging for stochastic integer programming Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-10-11 Jeffrey Christiansen, Brian Dandurand, Andrew Eberhard, Fabricio Oliveira
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Efficiency of higher-order algorithms for minimizing composite functions Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-10-10 Yassine Nabou, Ion Necoara
Composite minimization involves a collection of functions which are aggregated in a nonsmooth manner. It covers, as a particular case, smooth approximation of minimax games, minimization of max-type functions, and simple composite minimization problems, where the objective function has a nonsmooth component. We design a higher-order majorization algorithmic framework for fully composite problems (possibly
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The deepest event cuts in risk-averse optimization with application to radiation therapy design Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-10-04 Constantine A. Vitt, Darinka Dentcheva, Andrzej Ruszczyński, Nolan Sandberg
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Extension of switch point algorithm to boundary-value problems Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-09-30 William W. Hager
In an earlier paper (https://doi.org/10.1137/21M1393315), the switch point algorithm was developed for solving optimal control problems whose solutions are either singular or bang-bang or both singular and bang-bang, and which possess a finite number of jump discontinuities in an optimal control at the points in time where the solution structure changes. The class of control problems that were considered
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Linearly convergent bilevel optimization with single-step inner methods Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-09-28 Ensio Suonperä, Tuomo Valkonen
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Equilibrium modeling and solution approaches inspired by nonconvex bilevel programming Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-09-25 Stuart Harwood, Francisco Trespalacios, Dimitri Papageorgiou, Kevin Furman
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A numerical-and-computational study on the impact of using quaternions in the branch-and-prune algorithm for exact discretizable distance geometry problems Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-09-25 Felipe Fidalgo, Emerson Castelani, Guilherme Philippi
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Stochastic projective splitting Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-09-23 Patrick R. Johnstone, Jonathan Eckstein, Thomas Flynn, Shinjae Yoo
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Distribution-free algorithms for predictive stochastic programming in the presence of streaming data Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-09-22 Shuotao Diao, Suvrajeet Sen
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A nested genetic algorithm strategy for an optimal seismic design of frames Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-09-19 A. Greco, F. Cannizzaro, R. Bruno, A. Pluchino
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Inexact proximal DC Newton-type method for nonconvex composite functions Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-09-15 Shummin Nakayama, Yasushi Narushima, Hiroshi Yabe
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A Filippov approximation theorem for strengthened one-sided Lipschitz differential inclusions Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-09-11 Robert Baier, Elza Farkhi
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Stochastic inexact augmented Lagrangian method for nonconvex expectation constrained optimization Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-09-07 Zichong Li, Pin-Yu Chen, Sijia Liu, Songtao Lu, Yangyang Xu
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Multiobjective BFGS method for optimization on Riemannian manifolds Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-09-07 Shahabeddin Najafi, Masoud Hajarian
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Generalizations of the proximal method of multipliers in convex optimization Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-08-30 R. Tyrrell Rockafellar
The proximal method of multipliers, originally introduced as a way of solving convex programming problems with inequality constraints, is a proximally stabilized alternative to the augmented Lagrangian method that is sometimes called the proximal augmented Lagrangian method. It has gained attention as a vehicle for deriving decomposition algorithms for wider formulations of problems in convex optimization
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From Halpern’s fixed-point iterations to Nesterov’s accelerated interpretations for root-finding problems Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-08-23 Quoc Tran-Dinh
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A trust-region approach for computing Pareto fronts in multiobjective optimization Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-08-20 A. Mohammadi, A. L. Custódio
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Local convergence analysis of augmented Lagrangian method for nonlinear semidefinite programming Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-08-17 Shiwei Wang, Chao Ding
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Inexact proximal Newton methods in Hilbert spaces Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-08-16 Bastian Pötzl, Anton Schiela, Patrick Jaap
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A successive centralized circumcentered-reflection method for the convex feasibility problem Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-08-11 Roger Behling, Yunier Bello-Cruz, Alfredo Iusem, Di Liu, Luiz-Rafael Santos
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First order inertial optimization algorithms with threshold effects associated with dry friction Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-08-10 Samir Adly, Hedy Attouch, Manh Hung Le
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An easily computable upper bound on the Hoffman constant for homogeneous inequality systems Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-08-09 Javier F. Peña
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Distributed stochastic compositional optimization problems over directed networks Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-08-03 Shengchao Zhao, Yongchao Liu
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Spectral conjugate gradient methods for vector optimization problems Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-08-01 Qing-Rui He, Chun-Rong Chen, Sheng-Jie Li
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A modified inexact Levenberg–Marquardt method with the descent property for solving nonlinear equations Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-07-31 Jianghua Yin, Jinbao Jian, Guodong Ma
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A space–time variational method for optimal control problems: well-posedness, stability and numerical solution Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-07-25 Nina Beranek, Martin Alexander Reinhold, Karsten Urban
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A dual-based stochastic inexact algorithm for a class of stochastic nonsmooth convex composite problems Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-07-16 Gui-Hua Lin, Zhen-Ping Yang, Hai-An Yin, Jin Zhang
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Doubly majorized algorithm for sparsity-inducing optimization problems with regularizer-compatible constraints Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-07-13 Tianxiang Liu, Ting Kei Pong, Akiko Takeda
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Sparse optimization via vector k-norm and DC programming with an application to feature selection for support vector machines Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-07-12 Manlio Gaudioso, Giovanni Giallombardo, Giovanna Miglionico
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Complexity analysis of interior-point methods for second-order stationary points of nonlinear semidefinite optimization problems Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-07-12 Shun Arahata, Takayuki Okuno, Akiko Takeda
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Perturbation analysis of the euclidean distance matrix optimization problem and its numerical implications Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-07-11 Shaoyan Guo, Hou-Duo Qi, Liwei Zhang
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SCORE: approximating curvature information under self-concordant regularization Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-07-08 Adeyemi D. Adeoye, Alberto Bemporad
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A branch-and-prune algorithm for discrete Nash equilibrium problems Comput. Optim. Appl. (IF 2.2) Pub Date : 2023-07-07 Stefan Schwarze, Oliver Stein