Stochastic Programming Numerical Techniques and Engineering Applications
Título:
Stochastic Programming Numerical Techniques and Engineering Applications
ISBN:
9783642882722
Edición:
1st ed. 1995.
PRODUCTION_INFO:
Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 1995.
Descripción física:
IX, 351 p. 60 illus. online resource.
Serie:
Lecture Notes in Economics and Mathematical Systems, 423
Contenido:
From the contents: Theoretical Models: Types of Asymptotic Approximations for Normal Probability Integrals -- Strong Convexity and Directional Derivatives of Marginal Values in Two-Stage Stochastic Programming -- Numerical Methods and Computer Support: Computation of Probability Functions and its Dervatives by means of Orthogonal Function Series Expansions -- Computer Support for Modeling in Stochastic Linear Programming -- Structural Design via Evolution Strategies -- On the Regularized Decomposition Method for Stochastic Programming Problems -- Multipoint Approximation Method for Structural Optimization Problems with Noisy Function Values -- Sequential Convex Programming Methods -- Engineering Applications: Target Costing: The Data Problem -- Statistical Characterization of Granular Assemblies -- On Stochastic Aspects of a Metal Cutting Problem -- Consideration of Stochastic Effects for Finding Optimal Layouts of Mechanical Structures -- Tolerance Dynamics for a High Precision Balance -- On Boundary-Initial Value Problem for Linear Hyperbolic Thermoelasticity Equations with Control of Temperature.
Síntesis:
In order to obtain more reliable optimal solutions of concrete technical/economic problems, e.g. optimal design problems, the often known stochastic variations of many technical/economic parameters have to be taken into account already in the planning phase. Hence, ordinary mathematical programs have to be replaced by appropriate stochastic programs. New theoretical insight into several branches of reliability-oriented optimization of stochastic systems, new computational approaches and technical/economic applications of stochastic programming methods can be found in this volume.
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Full Text Available From Springer Nature Business and Economics Archive Packages
Idioma:
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