Results 31 to 40 of about 141,498 (264)
Distributed Interval Optimization Over Time-Varying Networks: A Numerical Programming Perspective
IEEE Access, 2023 In this study, we investigate a distributed interval optimization problem involving agents linked by a time-varying network, optimizing interval objective functions under global convex constraints.
Yinghui Wang +3 more
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Greedy sparsity-constrained optimization [PDF]
2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR), 2011 Sparsity-constrained optimization has wide applicability in machine learning, statistics, and signal processing problems such as feature selection and compressive Sensing. A vast body of work has studied the sparsity-constrained optimization from theoretical, algorithmic, and application aspects in the context of sparse estimation in linear models ...
Sohail Bahmani +2 more
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Constrained Multiobjective Biogeography Optimization Algorithm
The Scientific World Journal, 2014 Multiobjective optimization involves minimizing or maximizing multiple objective functions subject to a set of constraints. In this study, a novel constrained multiobjective biogeography optimization algorithm (CMBOA) is proposed.
Hongwei Mo +4 more
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Sensitivity-Based Change Detection for Dynamic Constrained Optimization
IEEE Access, 2020 In dynamic constrained optimization, changes may occur in either the objective function or constraint functions, or both. However, although research on dynamic optimization has been growing significantly, it is centered mainly around unconstrained ...
Noha Hamza, Ruhul Sarker, Daryl Essam
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QGOpt: Riemannian optimization for quantum technologies
SciPost Physics, 2021 Many theoretical problems in quantum technology can be formulated and addressed as constrained optimization problems. The most common quantum mechanical constraints such as, e.g., orthogonality of isometric and unitary matrices, CPTP property of ...
Ilia A. Luchnikov, Alexander Ryzhov, Sergey N. Filippov, Henni Ouerdane
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Porcellio scaber algorithm (PSA) for solving constrained optimization problems
MATEC Web of Conferences, 2017 In this paper, we extend a bio-inspired algorithm called the porcellio scaber algorithm (PSA) to solve constrained optimization problems, including a constrained mixed discrete-continuous nonlinear optimization problem.
Zhang Yinyan, Li Shuai, Guo Hongliang
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Energies, 2022 This paper proposes a modified quasi-opposition-based grey wolf optimization (mQOGWO) method to solve complex constrained optimization problems. The effectiveness of mQOGWO is examined on (i) 23 mathematical benchmark functions with different dimensions ...
Salil Madhav Dubey +2 more
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Spectrally Constrained Optimization
Journal of Scientific ComputingWe investigate how to solve smooth matrix optimization problems with general linear inequality constraints on the eigenvalues of a symmetric matrix. We present solution methods to obtain exact global minima for linear objective functions, i.e., $F(X) = \langle C, X \rangle$, and perform exact projections onto the eigenvalue constraint set.
Casey Garner +2 more
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Constrained Optimization of MIMO Training Sequences
EURASIP Journal on Advances in Signal Processing, 2007 Multiple-input multiple-output (MIMO) systems have shown a huge potential for increased spectral efficiency and throughput. With an increasing number of transmitting antennas comes the burden of providing training for channel estimation for coherent ...
Coon Justin P, Sandell Magnus
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MOOSE Optimization Module: Physics-constrained optimization
SoftwareXThe MOOSE Optimization Module integrates optimization capabilities within the MOOSE framework, enabling efficient and accurate physics-constrained optimization. This module leverages automatic differentiation to compute Jacobians and employs an automatic
Zachary M. Prince +4 more
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