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Mixed-Integer Optimization II, Section 3.7.1 (Dantzig-Wolfe decomposition, motivation and construction)

This audio or video file is copyrighted. Access is only allowed via computers of the Karlsruhe Institute of Technology (KIT).

Author

Oliver Stein

Participating institute

Institut für Operations Research (IOR)

Genre

Vorlesung

Description

Lectures on nonlinear mixed-integer optimization at Karlsruhe Institute of Technology

Duration (hh:mm:ss)

00:51:06

Series

Mixed-Integer Optimization II

Published on

20.09.2022

Subject area

Economics

License

KITopen Licence

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Media Type video/mp4
Duration 3066 s
Filename DIVA-2022-358_hd.mp4
File Size 359.126.552 byte
Frame Rate 25
Video Bitrate 800440 bps
Video Codec h264

Embed Code

Mixed-Integer Optimization II Episodes 1-31 of 31
Mixed-Integer Optimization II, Section 3.8.3 (Feasibility pump), Section 3.8.4 (Metaheuristics)
Mixed-Integer Optimization II, Section 3.8.3 (Feasibility pump), Section 3.8.4 (Metaheuristics)
Mixed-Integer Optimization II, Section 3.8.1 (Diving heuristics), Section 3.8.2 (Local branching)
Mixed-Integer Optimization II, Section 3.8.1 (Diving heuristics), Section 3.8.2 (Local branching)
Mixed-Integer Optimization II, Section 3.7.4 (Initialization)
Mixed-Integer Optimization II, Section 3.7.4 (Initialization)
Mixed-Integer Optimization II, Section 3.7.3 (Pricing)
Mixed-Integer Optimization II, Section 3.7.3 (Pricing)
Mixed-Integer Optimization II, Section 3.7.2 (Column generation)
Mixed-Integer Optimization II, Section 3.7.2 (Column generation)
Mixed-Integer Optimization II, Section 3.7.1 (Dantzig-Wolfe decomposition, motivation and construction)
Mixed-Integer Optimization II, Section 3.7.1 (Dantzig-Wolfe decomposition, motivation and construction)
Mixed-Integer Optimization II, Section 3.6.4 (A subgradient method)
Mixed-Integer Optimization II, Section 3.6.4 (A subgradient method)
Mixed-Integer Optimization II, Section 3.6.3 (Comparison to continuous relaxation)
Mixed-Integer Optimization II, Section 3.6.3 (Comparison to continuous relaxation)
Mixed-Integer Optimization II, Section 3.6.2 (Decomposition by Lagrange relaxation)
Mixed-Integer Optimization II, Section 3.6.2 (Decomposition by Lagrange relaxation)
Mixed-Integer Optimization II, Section 3.6.1 (Lagrange relaxation, construction and relaxation property)
Mixed-Integer Optimization II, Section 3.6.1 (Lagrange relaxation, construction and relaxation property)
Mixed-Integer Optimization II, Section 3.5.4 (Cutting plane method for MICP), part 2
Mixed-Integer Optimization II, Section 3.5.4 (Cutting plane method for MICP), part 2
Mixed-Integer Optimization II, Section 3.5.4 (Cutting plane method for MICP), part 1
Mixed-Integer Optimization II, Section 3.5.4 (Cutting plane method for MICP), part 1
Mixed-Integer Optimization II, Section 3.5.3 (Optimality cuts)
Mixed-Integer Optimization II, Section 3.5.3 (Optimality cuts)
Mixed-Integer Optimization II, Section 3.5.2 (Feasibility cuts)
Mixed-Integer Optimization II, Section 3.5.2 (Feasibility cuts)
Mixed-Integer Optimization II, Section 3.5.1 (Motivation of the Outer Approximation method)
Mixed-Integer Optimization II, Section 3.5.1 (Motivation of the Outer Approximation method)
Mixed-Integer Optimization II, Section 3.4.7 (Cutting plane method for MICP), part 2
Mixed-Integer Optimization II, Section 3.4.7 (Cutting plane method for MICP), part 2
Mixed-Integer Optimization II, Section 3.4.7 (Cutting plane method for MICP), part 1
Mixed-Integer Optimization II, Section 3.4.7 (Cutting plane method for MICP), part 1
Mixed-Integer Optimization II, Section 3.4.6 (Feasibility cuts)
Mixed-Integer Optimization II, Section 3.4.6 (Feasibility cuts)
Mixed-Integer Optimization II, Section 3.4.5 (Optimality cuts), part 3
Mixed-Integer Optimization II, Section 3.4.5 (Optimality cuts), part 3
Mixed-Integer Optimization II, Section 3.4.5 (Optimality cuts), part 2
Mixed-Integer Optimization II, Section 3.4.5 (Optimality cuts), part 2
Mixed-Integer Optimization II, Section 3.4.5 (Optimality cuts), part 1
Mixed-Integer Optimization II, Section 3.4.5 (Optimality cuts), part 1
Mixed-Integer Optimization II, Section 3.4.4 (A purely discrete problem equivalent to MICP)
Mixed-Integer Optimization II, Section 3.4.4 (A purely discrete problem equivalent to MICP)
Mixed-Integer Optimization II, Section 3.4.3 (A functional description of the reduced feasible set)
Mixed-Integer Optimization II, Section 3.4.3 (A functional description of the reduced feasible set)
Mixed-Integer Optimization II, Section 3.4.2 (Convexity of the reduced feasible set and of the reduced objective function)
Mixed-Integer Optimization II, Section 3.4.2 (Convexity of the reduced feasible set and of the reduced objective function)
Mixed-Integer Optimization II, Section 3.4.1 (Reduced feasible set and reduced objective function)
Mixed-Integer Optimization II, Section 3.4.1 (Reduced feasible set and reduced objective function)
Mixed-Integer Optimization II, Section 3.4 (Generalized Benders decomposition, Introduction)
Mixed-Integer Optimization II, Section 3.4 (Generalized Benders decomposition, Introduction)
Mixed-Integer Optimization II, Section 3.3.3 (The nonconvex case)
Mixed-Integer Optimization II, Section 3.3.3 (The nonconvex case)
Mixed-Integer Optimization II, Section 3.3.1 (B&B für MINLP - A conceptual algorithm), Section 3.3.2 (The convex case)
Mixed-Integer Optimization II, Section 3.3.1 (B&B für MINLP - A conceptual algorithm), Section 3.3.2 (The convex case)
Mixed-Integer Optimization II, Section 3.2 (Continuous relaxation and rounding)
Mixed-Integer Optimization II, Section 3.2 (Continuous relaxation and rounding)
Mixed-Integer Optimization II, Section 3.1 (Models in portfolio optimization)
Mixed-Integer Optimization II, Section 3.1 (Models in portfolio optimization)
Mixed-Integer Optimization II, Section 3 (Mixed-integer nonlinear optimization), Introduction
Mixed-Integer Optimization II, Section 3 (Mixed-integer nonlinear optimization), Introduction