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Constrained Optimization by the α Constrained Particle Swarm Optimizer
Journal of Advanced Computational Intelligence and Intelligent Informatics, 2005 In this study, α constrained particle swarm optimizer αPSO, which is the combination of the α constrained method and particle swarm optimization, is proposed to solve constrained optimization problems. The α constrained methods can convert algorithms for unconstrained problems to algorithms for constrained problems using the α level comparison, which ...
Tetsuyuki Takahama, Setsuko Sakai
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Approximate Inference and Constrained Optimization [PDF]
CoRR, 2003 Appears in Proceedings of the Nineteenth Conference on Uncertainty in Artificial Intelligence (UAI2003)
Heskes, T., Albers, C.A., Kappen, H.J.
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Equilibrium constrained optimization problems [PDF]
European Journal of Operational Research, 2006 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
S. Ilker Birbil +3 more
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Robust preconditioners for PDE-constrained optimization with limited observations [PDF]
, 2015 Regularization robust preconditioners for PDE-constrained optimization problems have been successfully developed. These methods, however, typically assume that observation data is available throughout the entire domain of the state equation.
Mardal, Kent-André +2 more
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Easy Particle Swarm Optimization for Nonlinear Constrained Optimization Problems
IEEE Access, 2021 Particle swarm optimization (PSO) is a popular stochastic approach for solving practical optimal problems from industries due to its effective performance and few hyperparameters.
Hsuan-Yu Tseng +3 more
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Stock Portfolio-Optimization Model by Mean-Semi-Variance Approach Using of Firefly Algorithm and Imperialist Competitive Algorithm [PDF]
International Journal of Business and Development Studies, 2018 Selecting approaches with appropriate accuracy and suitable speed for the purpose of making decision is one of the managers’ challenges. Also investing decision is one of the main decisions of managers and it can be referred to securities transaction in ...
Hassan Heidari, Laya Neshatizadeh
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Self-Scaling Variable Metric in Constrained Optimization [PDF]
Al-Rafidain Journal of Computer Sciences and Mathematics, 2020 In this paper, we investigated of a new self-scaling by use quasi-Newton method and conjugate gradient method. The new algorithm satisfies a quasi-newton condition and mutually conjugate, and practically proved its efficiency when compared with the well ...
Eman Hamed, Marwa Hamad
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Optimization of constrained density functional theory [PDF]
, 2016 Constrained density functional theory (cDFT) is a versatile electronic structure method that enables ground-state calculations to be performed subject to physical constraints. It thereby broadens their applicability and utility.
O'Regan, David D., Teobaldi, Gilberto
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Advances in Mechanical Engineering, 2018 A hierarchical optimization strategy is proposed to optimally design constrained layer damping materials patched on the base plate for minimizing sound radiation power.
Dongdong Zhang, Tang Qi, Ling Zheng
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Constrained Policy Optimization
CoRR, 2017 Accepted to ICML ...
Joshua Achiam +3 more
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