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Bounds for convex quadratic programming problems and some important applications
This paper proposes bounds for the objective function of convex quadratic programming problem (QPP) in general form. The method uses just the eigenvalues of the Hessian matrix. By use of the eigenvalues of the Hessian matrix and solving two simple...
A new nonlinear neural network for solving quadratic programming problems
This paper presents a new recurrent neural network for solving quadratic programming
problems. The new model is simpler and more intuitive than existing models and
converges very fast to exact primal and dual solutions....
A two-phase variable neighborhood search for solving nonlinear optimal control problems
and the successive quadratic programming, as the local search step. In the first phase, VNS starts with a completely random initial solution of control input values. To increase the accuracy of the solution obtained from the phase 1, some new time nodes are added...
A Robust Correntropy-based Method for Analyzing Multisample aCGH Data
This paper presents a new method for analyzing Array comparative genomic hybridization (aCGH) data
based on Correntropy. A new formulation based on low-rank aCGH data and Correntropy is proposed and
its ...
A variables neighborhood search algorithm for solving fuzzy quadratic programming problems using modified Kerre’s method
numbers, we show that to compare two LR fuzzy numbers, we do not need to compute the fuzzy maximum of two numbers
directly. We propose a new variable neighborhood search approach for solving fuzzy number quadratic programming problems
by using...
Solving fuzzy quadratic programming problems based on ABS algorithm
Recently, Ghanbari and Mahdavi-Amiri (Appl Math Model 34:3363–3375, 2010) gave the general compromised solution of
an LR fuzzy linear system using ABS algorithm. Here, using this general solution, we solve quadratic programming problems...
Quadratic programming with interval fuzzy parameters
This paper discusses the interval-fuzzy quadratic programming problems
where the cost coefficient, and constraint coefficient, and right-hand sides, are
represented by interval-fuzzy data. Since the parameters are interval...
A new nonlinear neural network for solving quadratic programming problems
This paper presents a new neural network for solving quadratic programming problems.The
new model has a simple form, furthermore it has a good convergence rate with a less
number calculation operation than the old models. It converges...
Duality in bipolar triangular fuzzy number quadratic programming problems
We discuss how to solve bipolar fuzzy quadratic programming problems, where the parameters are bipolar
triangular fuzzy numbers, making use of linear ranking functions. Also, we explore some duality properties of bipolar triangular fuzzy...
Solving fuzzy number quadratic programming problems using a variableneighborhood search algorithm
algorithm for solving fuzzy number quadratic programming problems. In our
algorithm, the local search is defined based on descent directions. We show the effectiveness of our
proposed method in comparison with some available methods by using a...