Results 11 to 20 of about 5,020,641 (311)
A sufficient conditions for global quadratic optimization
Croatian Operational Research Review, 2020 This paper is devoted to global optimality conditions for quadratic optimization problems in a real space of dimension n. More precisely, we are concerned with nonconvex quadratic optimization problems with linear constraints. We present some sufficient
Mourad Naffouti, Abdeljelil Baccari
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IEEE Access, 2021 In order to meet the performance requirements of global optimality and path smoothness in robot path planning, a new fusion algorithm of jump-A* algorithm and dynamic window approach is proposed.
Lisang Liu +7 more
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Global Optimization Requires Global Information [PDF]
Journal of Optimization Theory and Applications, 1998 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Stephens, C. P., Baritompa, W.
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Necessary and sufficient condition on global optimality without convexity and second order differentiability [PDF]
, 2012 The main goal of this paper is to give a necessary and sufficient condition of global optimality for unconstrained optimization problems, when the objective function is not necessarily convex. We use Gâteaux differentiability of the objective function
Burai, Pál
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Global Optimization on an Interval [PDF]
Journal of Optimization Theory and Applications, 2016 The problem is that of finding all global maxima of a continuously differentiable real valued objective function \(F(t)\) in a closed interval \([0, T]\) (this includes possible maxima on the boundary). For this, two auxiliary functions or \textit{adjoint variables} \(x(t),\) \(y(t)\) are introduced, solution of the initial value problems \[ x'(s ...
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Energy Reports, 2022 Desalination and atmospheric water harvesting technologies are highly desirable to produce freshwater for daily life activities and alleviate the global water crisis.
Trevor Hocksun Kwan +3 more
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Distributed global optimization (DGO) [PDF]
Proceedings of International Conference on Neural Networks (ICNN'96), 2002 A new technique of global optimization and its applications in particular to neural networks are presented. The algorithm is also compared to other global optimization algorithms such as Gradient descent (GD), Monte Carlo (MC), Genetic Algorithm (GA) and other commercial packages.
Homayoun Valafar +2 more
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Global Optimality in Low-Rank Matrix Optimization [PDF]
IEEE Transactions on Signal Processing, 2017 This paper considers the minimization of a general objective function $f(X)$ over the set of rectangular $n\times m$ matrices that have rank at most $r$. To reduce the computational burden, we factorize the variable $X$ into a product of two smaller matrices and optimize over these two matrices instead of $X$. Despite the resulting nonconvexity, recent
Zhihui Zhu +3 more
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IEEE Access, 2018 In this paper, we study the potential of non-orthogonal multiple access (NOMA) for the purpose of interference mitigation in downlink small cell networks (SCNs).
Xianling Wang +4 more
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Cooperative Output Regulation By Q-learning For Discrete Multi-agent Systems In Finite-time
Journal of Applied Science and Engineering, 2022 This article studies the output regulation of discrete-time multi-agent systems with an unknown model by a finite-time optimal control algorithm based on Q-learning that uses the method of the linear quadratic regulator (LQR).
Wenjun Wei, Jingyuan Tang
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