Use of chance-constrained programming to account for stochastic variation in the A-matrix of large-scale linear programs: A forestry application

DOI10.1007/BF02204867zbMath0726.90047OpenAlexW1975413906MaRDI QIDQ803038

James B. Pickens, Brian M. Kent, John G. Hof

Publication date: 1991

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

Full work available at URL: https://doi.org/10.1007/bf02204867

zbMATH Keywords

forestryMonte Carlo simulationchance-constrained approachrandom A-matrixstochastic production estimates

Mathematics Subject Classification ID

Large-scale problems in mathematical programming (90C06) Applications of mathematical programming (90C90) Stochastic programming (90C15) Production models (90B30) Case-oriented studies in operations research (90B90)

Uses Software

• IMSL Numerical Libraries
• SAS

Cites Work

• Chance-Constrained Programming with Joint Constraints
• Chance Constrained Programming with Joint Constraints
• Stochastic Linear Programming with Chance Constraints
• Deterministic Equivalents for Optimizing and Satisficing under Chance Constraints
• Unnamed Item
• Unnamed Item

This page was built for publication: Use of chance-constrained programming to account for stochastic variation in the A-matrix of large-scale linear programs: A forestry application