A cross-decomposition scheme with integrated primal-dual multi-cuts for two-stage stochastic programming investment planning problems

DOI10.1007/s10107-016-1001-yzbMath1347.90063OpenAlexW2314114783MaRDI QIDQ291046

Pablo Garcia-Herreros, Sumit Mitra, Ignacio E. Grossmann

Publication date: 6 June 2016

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

Full work available at URL: https://doi.org/10.1007/s10107-016-1001-y

zbMATH Keywords

two-stage stochastic programmingcross-decompositioninvestment planning

Mathematics Subject Classification ID

Applications of mathematical programming (90C90) Stochastic programming (90C15)

Related Items

A parallel hub-and-spoke system for large-scale scenario-based optimization under uncertainty, A hybrid genetic algorithm for scheduling jobs sharing multiple resources under uncertainty, The Benders Dual Decomposition Method, The Benders decomposition algorithm: a literature review, A new cross decomposition method for stochastic mixed-integer linear programming, A joint decomposition method for global optimization of multiscenario nonconvex mixed-integer nonlinear programs, Effects of feasibility cuts in Lagrangian relaxation for a two-stage stochastic facility location and network flow problem

Uses Software

• GAMS
• SITATION
• MOD-DIST
• MENU-OKF
• SUTIL

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Progress in computational mixed integer programming -- a look back from the other side of the tipping point
• On the convergence of cross decomposition
• About Lagrangian methods in integer optimization
• Proximity control in bundle methods for convex nondifferentiable minimization
• A lagrangean based branch-and-cut algorithm for global optimization of nonconvex mixed-integer nonlinear programs with decomposable structures
• A multicut algorithm for two-stage stochastic linear programs
• Partitioning procedures for solving mixed-variables programming problems
• Newton's method for convex programming and Tschebyscheff approximation
• Linear mean value cross decomposition: A generalization of the Kornai- Liptak method
• Mean value cross decomposition applied to integer programming problems
• Dual decomposition in stochastic integer programming
• The volume algorithm: Producing primal solutions with a subgradient method
• Scenario reduction algorithms in stochastic programming
• Lagrangean relaxation. (With comments and rejoinder).
• Multicut Benders decomposition algorithm for process supply chain planning under uncertainty
• The empirical behavior of sampling methods for stochastic programming
• Generalized Benders decomposition
• Grid-Enabled Optimization with GAMS
• Introduction to Stochastic Programming
• Mean Value Cross Decomposition for Two-Stage Stochastic Linear Programming with Recourse
• The Cutting-Plane Method for Solving Convex Programs
• Accelerating Benders method using covering cut bundle generation
• Lagrangean decomposition: A model yielding stronger lagrangean bounds
• Accelerating Benders Decomposition: Algorithmic Enhancement and Model Selection Criteria
• The Lagrangian Relaxation Method for Solving Integer Programming Problems
• Decomposition and Nondifferentiable Optimization with the Projective Algorithm
• A convergence proof for linear mean value cross decomposition
• Cross decomposition for mixed integer programming
• Validation of subgradient optimization
• Generalized Bundle Methods
• Stochastic Power Generation Unit Commitment in Electricity Markets: A Novel Formulation and a Comparison of Solution Methods
• L-Shaped Linear Programs with Applications to Optimal Control and Stochastic Programming
• The traveling-salesman problem and minimum spanning trees: Part II
• Canonical Cuts on the Unit Hypercube