Quadratic Programming (QP)
Quadratic Programming with Discrete Variables.
... binary quadratic programs (BQP) [30, 55, 56, ...of quadratic equality constraints, hence BQP also belongs to the class of continuous quadratic programming problems ...of QP, which have ...
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Robust Mvdr Beamformer for Nulling Level Control via Multi-Parametric Quadratic Programming
... to improve the nulling level control performances. This method can provide increased robustness against the mismatch problem as well as control over the sidelobe level. When the antenna platform vibrates or interference ...
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A Quadratic Programming with Triangular Fuzzy Numbers
... Quadratic Programming (QP) is a mathematical modeling technique de- signed to optimize the usage of limited resources and has been widely applied to solve real world ...conventional quadratic ...
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Conic Reformulation of Some Quadratic Programming Problems with Applications.
... non-convex quadratic programming programs with mixed binary and continuous variables as linear conic programming problem over the cone of completely positive matrices and proved the ...
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An accelerating algorithm for globally solving nonconvex quadratic programming
... initial quadratic programming problem is reduced to a sequence of linear relaxation programming problems, which is used to obtain a lower bound of the optimal value of this ...
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Quadratic Programming Feature Selection
... Identifying a subset of features that preserves classification accuracy is a problem of growing im- portance, because of the increasing size and dimensionality of real-world data sets. We propose a new feature selection ...
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Study on Fuzzy Quadratic Programming Problems
... fuzzy quadratic programming have aroused great attention from scholars, and it has yielded a series of good ...fuzzy programming, and Lagrange duality and KKT conditions of convex fuzzy ...
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Quadratic programming and penalized regression
... that quadratic programming can calculate penalised regression estimates with a variety of roughness penalties, in particular total variation denoising estimates, which use an L 1 ...
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A Solution Approach for Solving Fully Fuzzy Quadratic Programming Problems
... a Quadratic Programming problem. The classical Quadratic Programming problem is the problem of finding the minimum or maximum values of a quadratic function under constraints that are ...
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Some Properties of Interval Quadratic Programming Problem
... liner programming problems, Rohn proposed four equivalence relations regarding to the upper and lower bounds of the interval optimal ...interval quadratic programming problem have been ...
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Approximations of a quadratic programming problem with incomplete information
... small the gradient stopping rules perform better for more iterations, but when it is large they perform more erratically perhaps even getting worse with more iterations" Since the QP dec[r] ...
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Quadratically Constrained Quadratic Programming Problems and Extensions.
... ic programming framework using the cone of nonnegative quadratic ...conic programming problem, and proposed a computational scheme that may lead to an efficient al- gorithm for solving IQCQP problems ...
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An active set algorithm for a class of linear complementarity problems arising from rigid body dynamics
... linear programming (LP) and quadratic programming (QP); it has often been described as a fundamental problem Billups and Murty ...mathematical programming problems such as LP, convex ...
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Survey of Different Data Dependence Analysis Techniques
... Abstract—Dependency analysis is a technique to detect dependencies between tasks that prevent these tasks from running in parallel. It is an important aspect of parallel programming tools. Dependency analysis ...
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Solving the Binary Linear Programming Model in Polynomial Time
... linear programming (BLP) model is NP-complete and up to now we have not been aware of any po- lynomial algorithm for this ...convex quadratic programming (QP) ...convex QP is also the ...
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An Algorithm for NonparametricE stimation of A M ultivariateM ixing Distribution with Applications to P opulationP harmacokinetics
... NPAG Nonparametric adaptive grid algorithm NPML Nonparametric maximum likelihood PDIP Primal-dual interior point method. QP Quadratic programming[r] ...
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On Murty's gravitational interior point method for quadratic programming
... centering step is to determine point within the feasible region that has most possible. distance from boundaries of feasible region and at same time has the objective value[r] ...
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A Two Stage Approach for Large Scale Cascaded Hydropower System Operations
... with quadratic programming (QP) to improve the optimization ...of QP method employed at the second ...for QP me- thod is then determined, where the nonlinear water level function and ...
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Prevention of Voltage Instability by Using FACTS Controllers in Power Systems: A Literature Survey
... and quadratic programming, non-linear optimization programming, integer and mixed integer optimization programming, and dynamic optimization ...optimization programming techniques has ...
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Some recent developments in nonlinear optimization algorithms
... Abstract . This article provides a condensed overview of some of the major today’s features (both classical or recently developed), used in the design and development of algorithms to solve nonlinear continuous ...
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