A spectral conjugate gradient method for unconstrained optimization [PDF]
, 2015 A family of scaled conjugate gradient algorithms for large-scale unconstrained minimization is defined. The Ferry, the Polak-Ribiere and the Fletcher-Reeves formulae are compared using a spectral scaling derived from Raydan's spectral gradient ...
Birgin, EG, Martinez, JM
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A clustering particle swarm optimizer for dynamic optimization [PDF]
, 2009 This article is posted here with permission of the IEEE - Copyright @ 2009 IEEEIn the real world, many applications are nonstationary optimization problems.
Yang, S +5 more
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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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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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An alternative globalization strategy for unconstrained optimization [PDF]
, 2018 We propose a new globalization strategy that can be used in unconstrained optimization algorithms to support rapid convergence from remote starting points.
Öztoprak, Figen
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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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On the design of optimization strategies based on global response surface approximation models [PDF]
, 2005 Striking the correct balance between global exploration of search spaces and local exploitation of promising basins of attraction is one of the principal concerns in the design of global optimization algorithms.
András Sóbester +5 more
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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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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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