On Bridging the Gap Between Stochastic Integer Programming and MIP Solver Technologies

DOI10.1287/ijoc.1020.0005zbMath1239.90078OpenAlexW2166961583MaRDI QIDQ2890409

Gyana R. Parija, Alan J. King, Shabbir Ahmed

Publication date: 8 June 2012

Published in: INFORMS Journal on Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1287/ijoc.1020.0005

zbMATH Keywords

stochastic programminginteger programmingbranch and bound\texttt{OSLSE}

Mathematics Subject Classification ID

Integer programming (90C10) Polyhedral combinatorics, branch-and-bound, branch-and-cut (90C57) Stochastic programming (90C15)

Related Items (8)

PySP: modeling and solving stochastic programs in Python ⋮ On a stochastic sequencing and scheduling problem ⋮ Progressive hedging innovations for a class of stochastic mixed-integer resource allocation problems ⋮ In Memoriam: Shabbir Ahmed (1969–2019) ⋮ A Benders decomposition approach for solving the offshore wind farm installation planning at the North Sea ⋮ A stochastic multi-stage fixed charge transportation problem: worst-case analysis of the rolling horizon approach ⋮ Option pricing by mathematical programming† ⋮ Decision tree analysis for a risk averse decision maker: CVaR criterion

Uses Software

• MSLiP

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