Displaying similar documents to “Optimum Design of Steel Trusses”

A comparison between the continual reassessment method andD-optimum design for dose finding in phase I clinical trials

M. Iftakhar Alam (2016)

Biometrical Letters

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The continual reassessment method is a model-based procedure, described in the literature, used to determine the maximum tolerated dose in phase I clinical trials. The maximum tolerated dose can also be found under the framework of D-optimum design, where information is gathered in such a way so that asymptotic variability in the parameter estimates in minimised. This paper investigates the two methods under some realistic settings to explore any potential differences between them. Simulation...

Chance constrained optimal beam design: Convex reformulation and probabilistic robust design

Jakub Kůdela, Pavel Popela (2018)

Kybernetika

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In this paper, we are concerned with a civil engineering application of optimization, namely the optimal design of a loaded beam. The developed optimization model includes ODE-type constraints and chance constraints. We use the finite element method (FEM) for the approximation of the ODE constraints. We derive a convex reformulation that transforms the problem into a linear one and find its analytic solution. Afterwards, we impose chance constraints on the stress and the deflection of...

Optimization of power transmission systems using a multi-level decomposition approach

Alexandre Dolgui, Nikolai Guschinsky, Genrikh Levin (2007)

RAIRO - Operations Research

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We discuss the use of operations research methods for computer-aided design of mechanical transmission systems. We consider how to choose simultaneously transmission ratios and basic design parameters of transmission elements (diameters, widths, modules and tooth number for gears, diameters of shafts). The objectives, by the order of importance, are: to minimize the deviation of the obtained speeds from desired; to maximize the transmission life; to minimize the total mass. To...

Machine-learning in optimization of expensive black-box functions

Yoel Tenne (2017)

International Journal of Applied Mathematics and Computer Science

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Modern engineering design optimization often uses computer simulations to evaluate candidate designs. For some of these designs the simulation can fail for an unknown reason, which in turn may hamper the optimization process. To handle such scenarios more effectively, this study proposes the integration of classifiers, borrowed from the domain of machine learning, into the optimization process. Several implementations of the proposed approach are described. An extensive set of numerical...