Results 271 to 280 of about 10,265,072 (333)
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Operations Research, 1999
We present two new results for the asymmetric rendezvous problem on the line. We first show that it is never optimal for one player to be stationary during the entire search period in the two-player rendezvous. Then we consider the meeting time ofn-players in the worst case and show that it has an asymptotic behavior ofn/2 +O(logn).
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We present two new results for the asymmetric rendezvous problem on the line. We first show that it is never optimal for one player to be stationary during the entire search period in the two-player rendezvous. Then we consider the meeting time ofn-players in the worst case and show that it has an asymptotic behavior ofn/2 +O(logn).
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Balancing assembly lines with tabu search
European Journal of Operational Research, 2006zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Lapierre, Sophie D. +2 more
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On the Nonmonotone Line Search
Journal of Optimization Theory and Applications, 2002zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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2003
There is no guarantee that the local algorithms in chapters 12 and 13 will converge when they are started at a point x 1 far from a solution x * to problem (P E ) or (P EI ). They can generate erratic sequences, which may by chance enter the neighborhood of a solution and then converge to it; but most often, the sequences will not converge. There exist
J. Frédéric Bonnans +3 more
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There is no guarantee that the local algorithms in chapters 12 and 13 will converge when they are started at a point x 1 far from a solution x * to problem (P E ) or (P EI ). They can generate erratic sequences, which may by chance enter the neighborhood of a solution and then converge to it; but most often, the sequences will not converge. There exist
J. Frédéric Bonnans +3 more
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Journal of Optimization Theory and Applications, 2017
In this paper, we consider a class of possibly non-convex and non-smooth optimization problems arising in many contemporary applications such as machine learning, variable selection and image processing.
Lei Yang
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In this paper, we consider a class of possibly non-convex and non-smooth optimization problems arising in many contemporary applications such as machine learning, variable selection and image processing.
Lei Yang
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Distributed On-line Bayesian Search
2005 International Conference on Collaborative Computing: Networking, Applications and Worksharing, 2006In this paper, we outline the basis for a new distributed Bayesian search scheme in which all Bayesian decision makers recognize the same performance objective but do not possess the ability to communicate with each other. Coordination among the players is achieved indirectly by tracking search performance.
A. Garcia, E. Campos, null Chenyang Li
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Global convergence of Riemannian line search methods with a Zhang-Hager-type condition
Numerical Algorithms, 2022H. Oviedo
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The global convergence of the BFGS method with a modified WWP line search for nonconvex functions
Numerical Algorithms, 2022Gonglin Yuan, Pengyuan Li, Junyu Lu
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Convergence of the Exponentiated Gradient Method with Armijo Line Search
Journal of Optimization Theory and Applications, 2017Consider the problem of minimizing a convex differentiable function on the probability simplex, spectrahedron, or set of quantum density matrices. We prove that the exponentiated gradient method with Armijo line search always converges to the optimum, if
Yen-Huan Li, V. Cevher
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An adaptive nonmonotone line search for multiobjective optimization problems
Computers & Operations Research, 2021Nasim Ghalavand, E. Khorram, V. Morovati
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