Solving stochastic structural optimization problems by RSM-based stochastic approximation methods -- gradient estimation in case of intermediate variables

DOI10.1007/BF01194863zbMath0896.90176MaRDI QIDQ1386670

Kurt Marti

Publication date: 26 May 1998

Published in: Mathematical Methods of Operations Research (Search for Journal in Brave)

zbMATH Keywords

stochastic approximationresponse surface methodreliability-based structural optimization

Mathematics Subject Classification ID

Applications of mathematical programming (90C90) Stochastic programming (90C15) Reliability, availability, maintenance, inspection in operations research (90B25) Optimization problems in solid mechanics (74P99)

Related Items (3)

Optimal Design of Trusses by Using Stochastic Linear Programming Techniques ⋮ Implementable algorithm for stochastic optimization using sample average approximations ⋮ The Malliavin gradient method for the calibration of stochastic dynamical models

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Bonferroni inequalities
• Novel Concepts for Constraint Treatments and Approximations in Efficient Structural Synthesis
• Structural optimization: A new dual method using mixed variables
• The method of moving asymptotes—a new method for structural optimization
• Mathematical programming and the optimization of computer simulations
• Semi-srochastic approximation by the response surface methodology (RMS)
• Bounds for the Probability of a Union, with Applications
• Efficient approximation concepts using second order information

This page was built for publication: Solving stochastic structural optimization problems by RSM-based stochastic approximation methods -- gradient estimation in case of intermediate variables