A method for reliability-based optimization with multiple non-normal stochastic parameters: a simplified airshed management study

DOI10.1007/S00477-009-0304-4zbMath1416.62633OpenAlexW2082774198MaRDI QIDQ2002001

Panos Y. Papalambros, Steve J. Skerlos, Kuei-Yuan Chan

Publication date: 11 July 2019

Published in: Stochastic Environmental Research and Risk Assessment (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00477-009-0304-4

zbMATH Keywords

uncertaintyreliability-based design optimizationenvironmental policy decisionsjoint constraint reliabilitynon-normal uncertainty

Mathematics Subject Classification ID

Applications of statistics to environmental and related topics (62P12)

Related Items (1)

Optimal design and impact analysis of urban traffic regulations under ambient uncertainty

Uses Software

• ADVISOR

Cites Work

• Unnamed Item
• Unnamed Item
• Linear and nonlinear programming.
• Probabilistic risk and uncertainty analysis for bioremediation of four chlorinated ethenes in groundwater
• Survey of mathematical programming models in air pollution management
• The beta distribution -- a physically consistent model for human exposure to airborne contami\-nants
• Probabilistic-fuzzy health risk modeling
• Nonlinear programming without a penalty function.

This page was built for publication: A method for reliability-based optimization with multiple non-normal stochastic parameters: a simplified airshed management study