Results 31 to 40 of about 13,831 (172)
A UV-Method for a Class of Constrained Minimized Problems of Maximum Eigenvalue Functions
Journal of Function Spaces, 2017 In this paper, we apply the UV-algorithm to solve the constrained minimization problem of a maximum eigenvalue function which is the composite function of an affine matrix-valued mapping and its maximum eigenvalue.
Wei Wang +3 more
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The use of positive and negative penalty functions in solving constrained optimization problems and partial differential equations [PDF]
, 2009 The Rayleigh-Ritz Method together with the Penalty Function Method is used to investigate the use of different types of penalty parameters. The use of artificial springs as penalty parameters is a very well established procedure to model constraints in ...
Monterrubio Salazar, Luis Emilio
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Complexity, 2017 Network-structured optimization problems are found widely in engineering applications. In this paper, we investigate a nonconvex distributed optimization problem with inequality constraints associated with a time-varying multiagent network, in which each
Jueyou Li +3 more
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Machine Learning: Science and TechnologyPhysics-informed neural networks (PINNs) have attracted significant attention in scientific machine learning for their capability to solve forward and inverse problems governed by partial differential equations. However, the accuracy of PINN solutions is
Shota Deguchi, Mitsuteru Asai
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Automatic decrease of the penalty parameter in exact penalty function methods [PDF]
European Journal of Operational Research, 1995 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Mongeau, Marcel, Sartenaer, Annick
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Smoothing Approximation to the Square-Root Exact Penalty Function [PDF]
, 2016 In this paper, smoothing approximation to the square-root exact penalty functions is devised for inequality constrained optimization. It is shown that an approximately optimal solution of the smoothed penalty problem is an approximately optimal solution ...
Shujun Lian, Yaqiong Duan
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A unifying theory of exactness of linear penalty functions [PDF]
Optimization, 2015 This is a slightly edited version of Accepted Manuscript of an article published by Taylor & Francis in Optimization on 22/12/2015, available online: http://www.tandfonline.com/10.1080/02331934.2015.1122005. In this version, a remark was added after Proposition 3.6 (the original numbering was preserved), and a mistake in the proof of Theorem 3.17 ...
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Steering exact penalty DCA for nonsmooth DC optimization problems with equality and inequality constraints [PDF]
, 2023 We propose and study a version of the DCA (Difference-of-Convex functions Algorithm) using the $\ell_1$ penalty function for solving nonsmooth DC optimization problems with nonsmooth DC equality and inequality constraints.
Dolgopolik, M. V.
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IEEE Access, 2019 For the self-energy recycling (SER) untrusted relay network, a two-phase destination-based jamming (DBJ) protocol is proposed, in which the destination transmits the jamming signal to reduce the received SNR of the untrusted relay node in the first phase
Siyang Xu +4 more
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The Role of grossone in Nonlinear Programming and Exact Penalty Methods [PDF]
, 2022 xact penalty methods form an important class of methods for solving constrained optimization problems. Using penalty functions, the original constrained optimization problem can be transformed in an “equivalent” unconstrained problem.
De Leone, Renato
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