Results 11 to 20 of about 2,661 (250)
A Rank-Two Feasible Direction Algorithm for the Binary Quadratic Programming
Journal of Applied Mathematics, 2013 Based on the semidefinite programming relaxation of the binary quadratic programming, a rank-two feasible direction algorithm is presented. The proposed algorithm restricts the rank of matrix variable to be two in the semidefinite programming relaxation ...
Xuewen Mu, Yaling Zhang
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An Inexact Feasible Quantum Interior Point Method for Linearly Constrained Quadratic Optimization
Entropy, 2023 Quantum linear system algorithms (QLSAs) have the potential to speed up algorithms that rely on solving linear systems. Interior point methods (IPMs) yield a fundamental family of polynomial-time algorithms for solving optimization problems. IPMs solve a
Zeguan Wu +4 more
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Journal of Optimization, Differential Equations and Their ApplicationsThis paper proposes an extension of Zoutendijk’s Method of Feasible Directions (MFD) for solving linearly constrained multi-objective optimization problems.
Ramdani Zoubir +2 more
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Search direction optimization of power flow analysis based on physics-informed deep learning
International Journal of Electrical Power & Energy SystemsPower flow analysis is crucial for obtaining power system operation states and optimizing control measures. The increasing integration of renewable energy sources has resulted in a more complex power system, posing challenges to the computational ...
Baoliang Li +3 more
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Feasible Direction Methods for Constrained Nonlinear Optimization: Suggestions for Improvements.
, 2007 This thesis concerns the development of novel feasible direction type algorithms for constrained nonlinear optimization. The new algorithms are based upon enhancements of the search direction determination and the line search steps. The Frank-Wolfe method is popular for solving certain structured linearly constrained nonlinear problems, although its ...
Mitradjieva-Daneva, Maria
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Quantum Interior Point Methods for Semidefinite Optimization [PDF]
Quantum, 2023 We present two quantum interior point methods for semidefinite optimization problems, building on recent advances in quantum linear system algorithms. The first scheme, more similar to a classical solution algorithm, computes an inexact search direction ...
Brandon Augustino +3 more
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An extension of the method of feasible directions [PDF]
, 1975 In this contribution we are going to discuss the extension of the method of feasible directions[1],[2],[3] to programming problems involving an infinite number of constraints. Problems of this type arise frequently in applications. We shall be working with arbitrary convex approximations instead of with linearizations, simply to emphasize the fact that
E. Blum, Werner Oettli
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A feasible direction method for linear programming [PDF]
Operations Research Letters, 1984 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Murty, Katta G., Fathi, Yahya
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A Conjugate Gradient Type Method for the Nonnegative Constraints Optimization Problems
Journal of Applied Mathematics, 2013 We are concerned with the nonnegative constraints optimization problems. It is well known that the conjugate gradient methods are efficient methods for solving large-scale unconstrained optimization problems due to their simplicity and low storage ...
Can Li
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Methodology to Solve Multi-Dimentional Sphere Packing Problems [PDF]
Journal of Mechanical Engineering, 2019 This paper discusses the problem of optimally packing spheres of various dimensions into containers of arbitrary geometrical shapes. According to the international classification, this problem belongs to Sphere Packing Problems (SPPs).
Georgiy N. Yaskov
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