Results 11 to 20 of about 7,447,344 (290)
Testing approaches for global optimization of space trajectories [PDF]
, 2008 In this paper the procedures to test global search algorithms applied to space trajectory design problems are discussed. Furthermore, a number of performance indexes that can be used to evaluate the effectiveness of the tested algorithms are presented.
Vasile, M. +7 more
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On testing global optimization algorithms for space trajectory design [PDF]
, 2008 In this paper we discuss the procedures to test a global search algorithm applied to a space trajectory design problem. Then, we present some performance indexes that can be used to evaluate the effectiveness of global optimization algorithms.
Vasile, Massimiliano +2 more
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A Global Optimizer for Nanoclusters [PDF]
Frontiers in Chemistry, 2019 We have developed an algorithm to automatically build the global minimum and other low-energy minima of nanoclusters. This method is implemented in PyAR (https://github.com/anooplab/pyar) program. The global optimization in PyAR involves two parts, generation of several trial geometries and gradient-based local optimization of the trial geometries ...
Maya Khatun +2 more
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CoRR, 2022 We consider the problem of estimating a good maximizer of a black-box function given noisy examples. To solve such problems, we propose to fit a new type of function which we call a global optimization network (GON), defined as any composition of an invertible function and a unimodal function, whose unique global maximizer can be inferred in $\mathcal ...
Sen Zhao +3 more
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ANTIGONE: Algorithms for coNTinuous / Integer Global Optimization of Nonlinear Equations [PDF]
, 2014 This manuscript introduces ANTIGONE, Algorithms for coNTinuous/Integer Global Optimization of Nonlinear Equations, a general mixed-integer nonlinear global optimization framework. ANTIGONE is the evolution of the Global Mixed-Integer Quadratic Optimizer,
Floudas, Christodoulos A, Misener, Ruth
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A hybrid multiagent approach for global trajectory optimization [PDF]
, 2008 In this paper we consider a global optimization method for space trajectory design problems. The method, which actually aims at finding not only the global minimizer but a whole set of low-lying local minimizers(corresponding to a set of different design
Vasile, M. +4 more
core +1 more source
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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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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Learning to be Global Optimizer
CoRR, 2020 The advancement of artificial intelligence has cast a new light on the development of optimization algorithm. This paper proposes to learn a two-phase (including a minimization phase and an escaping phase) global optimization algorithm for smooth non-convex functions. For the minimization phase, a model-driven deep learning method is developed to learn
Haotian Zhang, Jianyong Sun, Zongben Xu
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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
openaire +3 more sources