Obtaining lower bounds from the progressive hedging algorithm for stochastic mixed-integer programs

DOI10.1007/s10107-016-1000-zzbMath1338.90282OpenAlexW2312120261MaRDI QIDQ291039

Dinakar Gade, Roger J.-B. Wets, Sarah M. Ryan, Jean-Paul Watson, David L. Woodruff, Gabriel A. Hackebeil

Publication date: 6 June 2016

Published in: Mathematical Programming. Series A. Series B (Search for Journal in Brave)

Full work available at URL: https://lib.dr.iastate.edu/imse_pubs/73

zbMATH Keywords

decomposition algorithmslower boundingstochastic mixed-integer programming

Mathematics Subject Classification ID

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

Related Items

Resource allocation when planning for simultaneous disasters, Risk-averse hub location: formulation and solution approach, On preparedness resource allocation planning for natural disaster relief under endogenous uncertainty with time-consistent risk-averse management, Scenario cluster Lagrangean decomposition for risk averse in multistage stochastic optimization, Decomposing Loosely Coupled Mixed-Integer Programs for Optimal Microgrid Design, Multicomponent Maintenance Optimization: A Stochastic Programming Approach, Lagrange dual bound computation for stochastic service network design, Progressive hedging for stochastic programs with cross-scenario inequality constraints, Stochastic dual dynamic integer programming, A parallelizable augmented Lagrangian method applied to large-scale non-convex-constrained optimization problems, 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, A Lagrangian decomposition scheme for choice-based optimization, A stochastic programming approach for chemotherapy appointment scheduling, A parallel hub-and-spoke system for large-scale scenario-based optimization under uncertainty, Combining penalty‐based and Gauss–Seidel methods for solving stochastic mixed‐integer problems, Ambulance location routing problem considering all sources of uncertainty: progressive estimating algorithm, On pricing-based equilibrium for network expansion planning. A multi-period bilevel approach under uncertainty, Quantitative stability of fully random two-stage stochastic programs with mixed-integer recourse, Deriving solution value bounds from the ADMM, Supporting platelet inventory management decisions: what is the effect of extending platelets' shelf life?, Optimizing vaccine distribution in developing countries under natural disaster risk, Scenario-dominance to multi-stage stochastic lot-sizing and knapsack problems, Optimization of covered calls under uncertainty, BBPH: using progressive hedging within branch and bound to solve multi-stage stochastic mixed integer programs, Combining Progressive Hedging with a Frank--Wolfe Method to Compute Lagrangian Dual Bounds in Stochastic Mixed-Integer Programming, A progressive hedging based branch-and-bound algorithm for mixed-integer stochastic programs, A parallel branch-and-fix coordination based matheuristic algorithm for solving large sized multistage stochastic mixed 0-1 problems, A stabilised scenario decomposition algorithm applied to stochastic unit commitment problems, A finite \(\epsilon\)-convergence algorithm for two-stage stochastic convex nonlinear programs with mixed-binary first and second-stage variables, A multistage stochastic programming approach for preventive maintenance scheduling of GENCOs with natural gas contract, On the time-consistent stochastic dominance risk averse measure for tactical supply chain planning under uncertainty, Soft clustering-based scenario bundling for a progressive hedging heuristic in stochastic service network design, Scheduled service network design with quality targets and stochastic travel times, A fully distributed asynchronous approach for multi-area coordinated network-constrained unit commitment, A scalable solution framework for stochastic transmission and generation planning problems, Lagrangian relaxation based heuristics for a chance-constrained optimization model of a hybrid solar-battery storage system, A multi-stage stochastic integer programming approach for locating electric vehicle charging stations, Optimization-Driven Scenario Grouping, A parallelized variable fixing process for solving multistage stochastic programs with progressive hedging, Stage-\(t\) scenario dominance for risk-averse multi-stage stochastic mixed-integer programs, Risk-averse stochastic programming and distributionally robust optimization via operator splitting, Multistage Stochastic Power Generation Scheduling Co-Optimizing Energy and Ancillary Services, Scenario Grouping and Decomposition Algorithms for Chance-Constrained Programs, Stochastic scheduling of chemotherapy appointments considering patient acuity levels

Uses Software

• Pyomo
• PySP
• ddsip

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
• Scenario grouping in a progressive hedging-based meta-heuristic for stochastic network design
• Scenario cluster decomposition of the Lagrangian dual in two-stage stochastic mixed 0-1 optimization
• Progressive hedging innovations for a class of stochastic mixed-integer resource allocation problems
• Applying the progressive hedging algorithm to stochastic generalized networks
• Dual decomposition in stochastic integer programming
• Progressive hedging and tabu search applied to mixed integer (0,1) multistage stochastic programming
• Integration of progressive hedging and dual decomposition in stochastic integer programs
• A finite branch-and-bound algorithm for two-stage stochastic integer programs
• PySP: modeling and solving stochastic programs in Python
• On parallelizing dual decomposition in stochastic integer programming
• Dynamic testing of wholesale power market designs: an open-source agent-based framework
• A stochastic programming approach for supply chain network design under uncertainty
• The million-variable ``march for stochastic combinatorial optimization
• Stochastic Network Interdiction
• Multiarea Stochastic Unit Commitment for High Wind Penetration in a Transmission Constrained Network
• Stochastic Optimization of Electricity Portfolios: Scenario Tree Modeling and Risk Management
• A Branch-and-Price Algorithm for Multistage Stochastic Integer Programming with Application to Stochastic Batch-Sizing Problems
• Reformulation and sampling to solve a stochastic network interdiction problem
• Decomposition Principle for Linear Programs
• Scenarios and Policy Aggregation in Optimization Under Uncertainty
• Lagrangean decomposition: A model yielding stronger lagrangean bounds
• Solving multistage stochastic networks: An application of scenario aggregation
• On the existence of optimal solutions to integer and mixed-integer programming problems
• Two‐stage stochastic integer programming: a survey
• A decomposition algorithm applied to planning the interdiction of stochastic networks