Integration of progressive hedging and dual decomposition in stochastic integer programs

DOI10.1016/j.orl.2015.03.008zbMath1408.90209OpenAlexW1993748657WikidataQ54961339 ScholiaQ54961339MaRDI QIDQ1785365

David L. Woodruff, Ge Guo, Jean-Paul Watson, Sarah M. Ryan, Gabriel A. Hackebeil

Publication date: 28 September 2018

Published in: Operations Research Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.orl.2015.03.008

zbMATH Keywords

stochastic programmingmixed-integer programmingdual decompositionlower boundingprogressive hedging

Mathematics Subject Classification ID

Mixed integer programming (90C11) Stochastic programming (90C15)

Related Items

Algorithmic innovations and software for the dual decomposition method applied to stochastic mixed-integer programs, Obtaining lower bounds from the progressive hedging algorithm for stochastic mixed-integer programs, State-Variable Modeling for a Class of Two-Stage Stochastic Optimization Problems, Lagrange dual bound computation for stochastic service network design, Some matheuristic algorithms for multistage stochastic optimization models with endogenous uncertainty and risk management, Resilient route design for collection of material from suppliers with split deliveries and stochastic demands, Combining penalty‐based and Gauss–Seidel methods for solving stochastic mixed‐integer problems, On Generating Lagrangian Cuts for Two-Stage Stochastic Integer Programs, Sampling Scenario Set Partition Dual Bounds for Multistage Stochastic Programs, A loose Benders decomposition algorithm for approximating two-stage mixed-integer recourse models, A progressive hedging based branch-and-bound algorithm for mixed-integer stochastic programs, Soft clustering-based scenario bundling for a progressive hedging heuristic in stochastic service network design, A matheuristic algorithm for stochastic home health care planning, Scheduled service network design with quality targets and stochastic travel times

Uses Software

• CPLEX
• Pyomo
• PySP
• ConicBundle
• ddsip

Cites Work

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