Results 21 to 30 of about 1,977,959 (288)
Goal seeking Quadratic Unconstrained Binary Optimization
Results in Control and Optimization, 2022 The Quadratic Unconstrained Binary Optimization (QUBO) modeling and solution framework is a requirement for quantum and digital annealers. However optimality for QUBO problems of any practical size is extremely difficult to achieve.
Amit Verma, Mark Lewis
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Nonlinear Conjugate Gradient Methods with Wolfe Type Line Search
Abstract and Applied Analysis, 2013 Nonlinear conjugate gradient method is one of the useful methods for unconstrained optimization problems. In this paper, we consider three kinds of nonlinear conjugate gradient methods with Wolfe type line search for unstrained optimization problems ...
Yuan-Yuan Chen, Shou-Qiang Du
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Global convergence properties of a Dai-Liao-type CGM for unconstrained optimization
Recent Advances in Natural SciencesA popular optimization technique called the conjugate gradient method (CGM) is renowned for its effectiveness in addressing problems involving unconstrained optimization.
Oluwaseun Biodun Onuoha
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An ensemble symbiosis organisms search algorithm and its application to real world problems [PDF]
Decision Science Letters, 2017 In this study, an ensemble algorithm has been proposed, called Quasi-Oppositional Symbiosis Organisms Search (QOSOS) algorithms, by incorporating the quasi-oppositional based learning (QOBL) strategy into the newly proposed Symbiosis Organisms Search ...
Sukanta Nama, Apu Kumar Saha
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A Class of Weighted Low Rank Approximation of the Positive Semidefinite Hankel Matrix
Journal of Applied Mathematics, 2015 We consider the weighted low rank approximation of the positive semidefinite Hankel matrix problem arising in signal processing. By using the Vandermonde representation, we firstly transform the problem into an unconstrained optimization problem and then
Jianchao Bai +3 more
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A modified three terms PRP conjugate gradient method
Journal of Hebei University of Science and Technology, 2018 In order to effectively solve a class of large-scale unconstrained optimization problems and overcome the shortcomings of other algorithms, such as complex algorithms, large memory and computer programming difficulties, a new search direction is defined,
Songhua WANG +3 more
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The Diagonal Update for Unconstrained Optimization [PDF]
مجلة التربية والعلم, 2012 In this research we introduced a new update of the Hessian matrix or we updating only the diagonal elements of Hessian matrix, and make the non-diagonal elements always equal to zero and in this case we can preserve the sparse property so called the ...
Saad Shakir Mahmood +2 more
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LARGE SCALE UNCONSTRAINED OPTIMIZATION
, 2009 This work is a survey on the methods for large scale unconstrained optimization. Besides its own theoretical importance, the growing interest in the last years in solving problems with a larger and larger number of variables are arising very frequently ...
ROMA, Massimo, Massimo Roma
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Modeling and Solution Strategies for Unconstrained Stochastic Optimization Problems [PDF]
, 1983 We review some modeling alternatives for handling risk in decision making processes for unconstrained stochastic optimization problems.
Wets, R.J.-B.
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Discrete Dynamics in Nature and Society, 2015 A new trust region method is presented, which combines nonmonotone line search technique, a self-adaptive update rule for the trust region radius, and the weighting technique for the ratio between the actual reduction and the predicted reduction.
Yunlong Lu +4 more
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