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Metaheuristics and large‐scale optimization
Technological and Economic Development of Economy, 2006 „Metaheuristics and large‐scale optimization" Technological and Economic Development of Economy, 12(1), p.
Leonidas Sakalauskas
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Large-Scale Portfolio Optimization Using Biogeography-Based Optimization
International Journal of Financial Studies, 2023 Portfolio optimization is a mathematical formulation whose objective is to maximize returns while minimizing risks. A great deal of improvement in portfolio optimization models has been made, including the addition of practical constraints. As the number
Wendy Wijaya, Kuntjoro Adji Sidarto
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Dynamic Factorization in Large-Scale Optimization [PDF]
Mathematical Programming, 1992 Mathematical Programming, 64, pp. 17-51.Factorization of linear programming (LP) models enables a large portion of the LP tableau to be represented implicitly and generated from the remaining explicit part. Dynamic factorization admits algebraic elements
Brown, Gerald G., Olson, Michael
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Spectral proximal method for solving large scale sparse optimization [PDF]
ITM Web of Conferences, 2021 In this paper, we propose to use spectral proximal method to solve sparse optimization problems. Sparse optimization refers to an optimization problem involving the ι0 -norm in objective or constraints.
Woo Gillian Yi Han +3 more
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Evolutionary Advantages of Stimulus-Driven EEG Phase Transitions in the Upper Cortical Layers
Frontiers in Systems Neuroscience, 2021 Spatio-temporal brain activity monitored by EEG recordings in humans and other mammals has identified beta/gamma oscillations (20–80 Hz), which are self-organized into spatio-temporal structures recurring at theta/alpha rates (4–12 Hz).
Robert Kozma +3 more
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Enriched Algorithms for Large Scale Unconstrained Optimization [PDF]
Al-Rafidain Journal of Computer Sciences and Mathematics, 2007 A new method for solving Large-Scale problems in the unconstrained optimization has been proposed in this research depending on the BFGS method. The limited memory is used in the BFGS method by multiplying the BFGS matrix by a vector to obtain vectors ...
Abbas Al-Bayati, Omar Mohammad
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Mathematics, 2023 Optimizing large-scale numerical problems is a significant challenge with numerous real-world applications. The optimization process is complex due to the multi-dimensional search spaces and possesses several locally optimal regions.
Martín Montes Rivera +3 more
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New Hybrid Quasi-Newton Algorithms for Large Scale Optimization [PDF]
Al-Rafidain Journal of Computer Sciences and Mathematics, 2009 Two new hybrid algorithms have been suggested in this paper, the first one utilizes four formula of self-scaling update matrix was used. The matrix is selected according to Buckley method in each step.
Abbas Al-Bayati, Sawsan Ismail
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Spread-based elite opposite swarm optimizer for large scale optimization
Cognitive Robotics, 2022 To prevent the traditional particle swarm optimizer (PSO) from inefficient search in complex problem spaces, this paper presents a novel spread-based elite opposite swarm optimizer (SEOSO) for large scale optimization.
Li Zhang, Yu Tan
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Evolutionary multiobjective optimization via efficient sampling-based offspring generation
Complex & Intelligent Systems, 2023 With the rising number of large-scale multiobjective optimization problems from academia and industries, some evolutionary algorithms (EAs) with different decision variable handling strategies have been proposed in recent years. They mainly emphasize the
Cheng He +3 more
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