2004, ISBN 9780691070780, xviii, 370

...) as possible - and how mathematicians over the centuries have struggled to calculate these problems of minima and maxima...

Maxima and minima | Mathematics | History & Philosophy | History

Maxima and minima | Mathematics | History & Philosophy | History

Book

2011, ISBN 052117984X, xiii, 306

.... This book analyses the problem of harm in world politics which stems from the fact that societies require the power to harm in order to defend themselves from internal and external threats, but must...

Harm reduction | Moral and ethical aspects | Political aspects | International relations | Justice | Violence

Harm reduction | Moral and ethical aspects | Political aspects | International relations | Justice | Violence

Book

2016, 1, ISBN 9781783534913, xx, 214 pages

... Else’s Problem calls for a radical change in how we think about our material world, and how we design, make and use the products and services we need...

Sustainable design | Environmental aspects | Consumption (Economics) | Consumption (Economics)\xSocial aspects | Waste minimization | Sustainability | Corporate Social Responsibility & Business Ethics | Environment & Business | Social aspects

Sustainable design | Environmental aspects | Consumption (Economics) | Consumption (Economics)\xSocial aspects | Waste minimization | Sustainability | Corporate Social Responsibility & Business Ethics | Environment & Business | Social aspects

Book

Foundations of computational mathematics, ISSN 1615-3375, 2012, Volume 12, Issue 6, pp. 805 - 849

In applications throughout science and engineering one is often faced with the challenge of solving an ill-posed inverse problem, where the number of available measurements is smaller...

60D05 | Semidefinite programming | Economics general | 52A41 | Linear and Multilinear Algebras, Matrix Theory | Mathematics | Real algebraic geometry | 41A45 | Convex optimization | 90C25 | Numerical Analysis | 90C22 | Atomic norms | Math Applications in Computer Science | Applications of Mathematics | Computer Science, general | Gaussian width | Symmetry | MATHEMATICS, APPLIED | CUT | APPROXIMATION | ALGORITHM | EQUATIONS | RANK | SPACE | MATHEMATICS | RECOVERY | MINIMIZATION | NORM | COMPUTER SCIENCE, THEORY & METHODS | Geometry | Computational mathematics | Algebra | Optimization | Inverse problems | Mathematical analysis | Norms | Programming | Mathematical models | Matrices | Atomic structure | Matrix methods

60D05 | Semidefinite programming | Economics general | 52A41 | Linear and Multilinear Algebras, Matrix Theory | Mathematics | Real algebraic geometry | 41A45 | Convex optimization | 90C25 | Numerical Analysis | 90C22 | Atomic norms | Math Applications in Computer Science | Applications of Mathematics | Computer Science, general | Gaussian width | Symmetry | MATHEMATICS, APPLIED | CUT | APPROXIMATION | ALGORITHM | EQUATIONS | RANK | SPACE | MATHEMATICS | RECOVERY | MINIMIZATION | NORM | COMPUTER SCIENCE, THEORY & METHODS | Geometry | Computational mathematics | Algebra | Optimization | Inverse problems | Mathematical analysis | Norms | Programming | Mathematical models | Matrices | Atomic structure | Matrix methods

Journal Article

Management Science, ISSN 1526-5501, 2005, Volume 51, Issue 10, pp. 1556 - 1571

.... This paper provides integer programming formulations and optimal solution algorithms for these problems...

algorithms | hub arc location | hub location | network design | integer programming formulations | Datasets | Unit costs | Integer programming | Mathematical sequences | Algorithms | Optimal solutions | Management science | Minimization of cost | Collection acquisitions | Cost efficiency | Network design | Integer programming formulations | Hub location | Hub arc location | DESIGN | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | MANAGEMENT | NETWORK LOADING PROBLEM | FLOW PROBLEM | hub arc location; hub location; network design; integer programming formulations; algorithms | Models | Management | Network hubs | Design | Studies | Transportation | Scheduling | Communications networks

algorithms | hub arc location | hub location | network design | integer programming formulations | Datasets | Unit costs | Integer programming | Mathematical sequences | Algorithms | Optimal solutions | Management science | Minimization of cost | Collection acquisitions | Cost efficiency | Network design | Integer programming formulations | Hub location | Hub arc location | DESIGN | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | MANAGEMENT | NETWORK LOADING PROBLEM | FLOW PROBLEM | hub arc location; hub location; network design; integer programming formulations; algorithms | Models | Management | Network hubs | Design | Studies | Transportation | Scheduling | Communications networks

Journal Article

Mathematical programming, ISSN 1436-4646, 2011, Volume 137, Issue 1-2, pp. 91 - 129

...–Łojasiewicz inequality. This assumption allows to cover a wide range of problems, including nonsmooth semi-algebraic...

Tame optimization | 65K15 | Theoretical, Mathematical and Computational Physics | Alternating minimization | Mathematics | Forward–backward splitting | Descent methods | 90C53 | Mathematical Methods in Physics | Iterative thresholding | Calculus of Variations and Optimal Control; Optimization | Proximal algorithms | Sufficient decrease | Combinatorics | 47J25 | Kurdyka–Łojasiewicz inequality | o-minimal structures | Nonconvex nonsmooth optimization | 34G25 | Semi-algebraic optimization | 47J30 | Mathematics of Computing | 90C25 | Numerical Analysis | Block-coordinate methods | Relative error | 49M15 | 49M37 | 47J35 | Kurdyka-Łojasiewicz inequality | Forward-backward splitting | MATHEMATICS, APPLIED | Kurdyka-Lojasiewicz inequality | COMPUTER SCIENCE, SOFTWARE ENGINEERING | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | MINIMIZATION | POINT ALGORITHM | Methods | Algorithms | Studies | Algebra | Analysis | Data smoothing | Optimization | Mathematical programming | Splitting | Gauss-Seidel method | Mathematical analysis | Minimization | Descent | Convergence

Tame optimization | 65K15 | Theoretical, Mathematical and Computational Physics | Alternating minimization | Mathematics | Forward–backward splitting | Descent methods | 90C53 | Mathematical Methods in Physics | Iterative thresholding | Calculus of Variations and Optimal Control; Optimization | Proximal algorithms | Sufficient decrease | Combinatorics | 47J25 | Kurdyka–Łojasiewicz inequality | o-minimal structures | Nonconvex nonsmooth optimization | 34G25 | Semi-algebraic optimization | 47J30 | Mathematics of Computing | 90C25 | Numerical Analysis | Block-coordinate methods | Relative error | 49M15 | 49M37 | 47J35 | Kurdyka-Łojasiewicz inequality | Forward-backward splitting | MATHEMATICS, APPLIED | Kurdyka-Lojasiewicz inequality | COMPUTER SCIENCE, SOFTWARE ENGINEERING | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | MINIMIZATION | POINT ALGORITHM | Methods | Algorithms | Studies | Algebra | Analysis | Data smoothing | Optimization | Mathematical programming | Splitting | Gauss-Seidel method | Mathematical analysis | Minimization | Descent | Convergence

Journal Article

Mathematical programming, ISSN 1436-4646, 2013, Volume 146, Issue 1-2, pp. 459 - 494

We introduce a proximal alternating linearized minimization (PALM) algorithm for solving a broad class of nonconvex and nonsmooth minimization problems...

Gauss-Seidel method | Kurdyka–Łojasiewicz property | Theoretical, Mathematical and Computational Physics | Block coordinate descent | Alternating minimization | Mathematics | 90C26 | Nonconvex-nonsmooth minimization | Proximal forward-backward | Mathematical Methods in Physics | 90C30 | Calculus of Variations and Optimal Control; Optimization | Mathematics of Computing | Numerical Analysis | 65K10 | 49M27 | 49M37 | Combinatorics | 47J25 | Sparse nonnegative matrix factorization | Kurdyka-Łojasiewicz property | MATHEMATICS, APPLIED | DECOMPOSITION | ALGORITHMS | Kurdyka-Lojasiewicz property | COMPUTER SCIENCE, SOFTWARE ENGINEERING | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | CONVERGENCE | NONNEGATIVE MATRIX FACTORIZATION | Analysis | Management science | Algorithms | Studies | Data smoothing | Mathematical programming | Functions (mathematics) | Construction | Mathematical analysis | Palm | Byproducts | Minimization | Optimization | Optimization and Control

Gauss-Seidel method | Kurdyka–Łojasiewicz property | Theoretical, Mathematical and Computational Physics | Block coordinate descent | Alternating minimization | Mathematics | 90C26 | Nonconvex-nonsmooth minimization | Proximal forward-backward | Mathematical Methods in Physics | 90C30 | Calculus of Variations and Optimal Control; Optimization | Mathematics of Computing | Numerical Analysis | 65K10 | 49M27 | 49M37 | Combinatorics | 47J25 | Sparse nonnegative matrix factorization | Kurdyka-Łojasiewicz property | MATHEMATICS, APPLIED | DECOMPOSITION | ALGORITHMS | Kurdyka-Lojasiewicz property | COMPUTER SCIENCE, SOFTWARE ENGINEERING | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | CONVERGENCE | NONNEGATIVE MATRIX FACTORIZATION | Analysis | Management science | Algorithms | Studies | Data smoothing | Mathematical programming | Functions (mathematics) | Construction | Mathematical analysis | Palm | Byproducts | Minimization | Optimization | Optimization and Control

Journal Article

Journal of mathematical imaging and vision, ISSN 1573-7683, 2010, Volume 40, Issue 1, pp. 120 - 145

In this paper we study a first-order primal-dual algorithm for non-smooth convex optimization problems with known saddle-point structure...

Reconstruction | Inverse problems | Control , Robotics, Mechatronics | Convex optimization | Computer Science | Image Processing and Computer Vision | Computer Imaging, Vision, Pattern Recognition and Graphics | Artificial Intelligence (incl. Robotics) | Total variation | Dual approaches | Image | MATHEMATICS, APPLIED | PROXIMAL POINT ALGORITHM | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | COMPUTER SCIENCE, SOFTWARE ENGINEERING | MINIMIZATION | MONOTONE-OPERATORS | SOAP FILMS | Graphics software | Algorithms | Image processing | Mathematical optimization

Reconstruction | Inverse problems | Control , Robotics, Mechatronics | Convex optimization | Computer Science | Image Processing and Computer Vision | Computer Imaging, Vision, Pattern Recognition and Graphics | Artificial Intelligence (incl. Robotics) | Total variation | Dual approaches | Image | MATHEMATICS, APPLIED | PROXIMAL POINT ALGORITHM | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | COMPUTER SCIENCE, SOFTWARE ENGINEERING | MINIMIZATION | MONOTONE-OPERATORS | SOAP FILMS | Graphics software | Algorithms | Image processing | Mathematical optimization

Journal Article

Applied energy, ISSN 0306-2619, 2015, Volume 147, Issue C, pp. 536 - 555

.... This paper provides a review on the most relevant research works conducted to solve natural gas transportation problems via pipeline systems...

Line-packing problem | Pooling problem | Fuel cost minimization problem | Operations research | Natural gas transportation | Pipeline optimization | OPTIMAL OPERATION | OPTIMAL-DESIGN | ENERGY & FUELS | PIPELINE SYSTEMS | MODEL-PREDICTIVE CONTROL | TRANSIENT ANALYSIS | ENGINEERING, CHEMICAL | PROGRAMMING-MODEL | FUEL CONSUMPTION | GLOBAL OPTIMIZATION | TRANSMISSION NETWORKS | Gas industry | Analysis | Natural gas | Management science | Gas transmission industry | MATHEMATICS AND COMPUTING | Mixed-integer linear programming | Line-pack | Mixed-integer nonlinear programming | Steady-state models | Pipeline Optimization | Nonlinear programming | 03 NATURAL GAS | Transmission systems | Transient models

Line-packing problem | Pooling problem | Fuel cost minimization problem | Operations research | Natural gas transportation | Pipeline optimization | OPTIMAL OPERATION | OPTIMAL-DESIGN | ENERGY & FUELS | PIPELINE SYSTEMS | MODEL-PREDICTIVE CONTROL | TRANSIENT ANALYSIS | ENGINEERING, CHEMICAL | PROGRAMMING-MODEL | FUEL CONSUMPTION | GLOBAL OPTIMIZATION | TRANSMISSION NETWORKS | Gas industry | Analysis | Natural gas | Management science | Gas transmission industry | MATHEMATICS AND COMPUTING | Mixed-integer linear programming | Line-pack | Mixed-integer nonlinear programming | Steady-state models | Pipeline Optimization | Nonlinear programming | 03 NATURAL GAS | Transmission systems | Transient models

Journal Article

SIAM journal on optimization, ISSN 1095-7189, 2012, Volume 22, Issue 2, pp. 341 - 362

In this paper we propose new methods for solving huge-scale optimization problems...

Google problem | Fast gradient schemes | Convex optimization | Coordinate relaxation | Worst-case efficiency estimates | MATHEMATICS, APPLIED | worst-case efficiency estimates | MINIMIZATION | fast gradient schemes | convex optimization | CONVERGENCE | coordinate relaxation

Google problem | Fast gradient schemes | Convex optimization | Coordinate relaxation | Worst-case efficiency estimates | MATHEMATICS, APPLIED | worst-case efficiency estimates | MINIMIZATION | fast gradient schemes | convex optimization | CONVERGENCE | coordinate relaxation

Journal Article

Proceedings of the IEEE, ISSN 0018-9219, 06/2010, Volume 98, Issue 6, pp. 948 - 958

The goal of the sparse approximation problem is to approximate a target signal using a linear combination of a few elementary signals drawn from a fixed collection...

Electrical engineering | Dictionaries | Matching pursuit algorithms | Mathematics | matching pursuit | Least squares approximation | Statistics | Inverse problems | Signal processing algorithms | Signal processing | sparse approximation | Approximation algorithms | convex optimization | Compressed sensing | Sparse approximation | Convex optimization | Matching pursuit | REPRESENTATIONS | RECONSTRUCTION | SIGNAL RECOVERY | THRESHOLDING ALGORITHM | MINIMIZATION PROBLEMS | ENGINEERING, ELECTRICAL & ELECTRONIC | PURSUIT | SHRINKAGE | UNCERTAINTY PRINCIPLES | SELECTION | Algorithms | Approximation | Computation | Mathematical analysis | Collection | Mathematical models

Electrical engineering | Dictionaries | Matching pursuit algorithms | Mathematics | matching pursuit | Least squares approximation | Statistics | Inverse problems | Signal processing algorithms | Signal processing | sparse approximation | Approximation algorithms | convex optimization | Compressed sensing | Sparse approximation | Convex optimization | Matching pursuit | REPRESENTATIONS | RECONSTRUCTION | SIGNAL RECOVERY | THRESHOLDING ALGORITHM | MINIMIZATION PROBLEMS | ENGINEERING, ELECTRICAL & ELECTRONIC | PURSUIT | SHRINKAGE | UNCERTAINTY PRINCIPLES | SELECTION | Algorithms | Approximation | Computation | Mathematical analysis | Collection | Mathematical models

Journal Article

Applied Mathematics and Computation, ISSN 0096-3003, 04/2015, Volume 256, pp. 472 - 487

.... By using a product space approach we employ these results to the solving of monotone inclusion problems involving linearly composed and parallel-sum type operators and provide in this way iterative...

Douglas–Rachford splitting | Krasnosel’skiı̆–Mann algorithm | Convex optimization | Primal–dual algorithm | Inertial splitting algorithm | Krasnosel'skiѣ-Mann algorithm Primal-dual algorithm Convex optimization | Douglas-Rachford splitting | MATHEMATICS, APPLIED | Primal-dual algorithm | Krasnosel'skii-Mann algorithm | MINIMIZATION | WEAK-CONVERGENCE | PROXIMAL POINT ALGORITHM | OPERATORS | COMPOSITE

Douglas–Rachford splitting | Krasnosel’skiı̆–Mann algorithm | Convex optimization | Primal–dual algorithm | Inertial splitting algorithm | Krasnosel'skiѣ-Mann algorithm Primal-dual algorithm Convex optimization | Douglas-Rachford splitting | MATHEMATICS, APPLIED | Primal-dual algorithm | Krasnosel'skii-Mann algorithm | MINIMIZATION | WEAK-CONVERGENCE | PROXIMAL POINT ALGORITHM | OPERATORS | COMPOSITE

Journal Article