 Stochastic Structural Optimization with Quadratic Loss FunctionsKurt Marti
Chapter Chapter 7 in Stochastic Optimization Methods, 2015, pp 289-322 from Springer Abstract: Abstract Problems from plastic analysis and optimal plastic design are based on the convex, linear or linearized yield/strength condition and the linear equilibrium equation for the stress (state) vector. In practice one has to take into account stochastic variations of several model parameters. Hence, in order to get robust optimal decisions, the structural optimization problem with random parameters must be replaced by an appropriate deterministic substitute problem. A direct approach is proposed based on the primary costs (weight, volume, costs of construction, costs for missing carrying capacity, etc.) and the recourse costs (e.g. costs for repair, compensation for weakness within the structure, damage, failure, etc.). Based on the mechanical survival conditions of plasticity theory, a quadratic error/loss criterion is developed. The minimum recourse costs can be determined then by solving an optimization problem having a quadratic objective function and linear constraints. Keywords: Cost Function; Feasibility Condition; Total Cost Function; Plane Frame; Quadratic Objective Function (search for similar items in EconPapers) There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-662-46214-0_7 Ordering information: This item can be ordered from DOI: 10.1007/978-3-662-46214-0_7 Access Statistics for this chapter More chapters in Springer Books from Springer |
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