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Wolf, Christian: Advanced acceleration techniques for Nested Benders decomposition in stochastic programming. 2014
Content
Introduction
Fundamentals
Stochastic Programming Preliminaries
Mathematical Programs
Stochastic Programs
Basic Probability Theory
Two-Stage Stochastic Programs
Multi-Stage Stochastic Programs
Basic Properties
Solution Methods
Scenario Tree
Deterministic Equivalent
Benders Decomposition
Lagrangean Relaxation
Approximative Solution Methods
Exterior Sampling
Interior Sampling
Scenario Tree Generation
State-of-the-Art
Benders Decomposition
Notational Reconcilation
Aggregates
Stabilizing the master problem
Regularized Decomposition
Level Decomposition
Trust-Region Method
Cut Generation
Solving Similar Subproblems
Nested Benders Decomposition
Nested L-shaped method
Sequencing Protocols
Parallelization
Advanced Start
Stage Aggregation
Modeling Languages
Theoretical Concepts
Practical Examples
Required Work
Solver Development
Modeling Languages
Advanced Techniques and Computational Results
Accelerating the Nested Benders Decomposition
Cut Consolidation
Dynamic Sequencing
Parallelization
Aggregation
On-Demand Accuracy
Level decomposition
Extending techniques to the multi-stage case
A Modeling Environment for Stochastic Programs
Computational Results
Test Instances
Evaluation Techniques
Implementation Aspects
Implementation
Solving a subproblem
Warm Start
Tolerances
Computing environment
Evaluation of Two-Stage Acceleration Techniques
Cut Aggregation
Cut consolidation
Level decomposition
On-demand accuracy
Advanced start solution
Effect of Parallelization
Evaluation of Multi-Stage Acceleration Techniques
Sequencing protocols
SAA and Parallel Benders
Conclusion
Summary and Conclusion
Bibliography
Test problems
Test Results
List of Figures
List of Tables
List of Algorithms
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