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Nature-inspired optimization methods, Vorlesung SS 2020

Author

Pradyumn Shukla

Genre

Vorlesung

Description

Vorlesung Nature-inspired optimization methods SS 2020

Subject area

Economics

License

KITopen Licence

Note

You can subscribe to the contributions of this series as a podcast.

Embed Code

<iframe width="640" height="360" src="https://medienportal.bibliothek.kit.edu/play/DIVA-2020-C23" allowFullScreen="true" style="border: 0; overflow: hidden;"></iframe>

Episodes 1-14 of 14

Chapter: Modelling fairness in resource allocation problems, Vorlesung SS 2020, 16.07.2020

Chapter: Robust design optimization, Vorlesung SS 2020, 11.07.2020

Chapter: An algorithmic framework for many-objective optimization, Vorlesung SS 2020, 10.07.2020

Chapter: Constraint handling techniques, Vorlesung SS 2020, 09.07.2020

Chapter: User preferences, distributed computing, Vorlesung SS 2020, 05.07.2020

Chapter: Multi-objective Evolutionary Algorithms, Vorlesung SS 2020, 04.07.2020

Chapter: Evolutionary algorithms, Part II, Vorlesung SS 2020, 10.06.2020

Chapter: Evolutionary algorithms, Part I, Vorlesung SS 2020, 30.05.2020

Chapter: Escaping Local Minima. II. Tabu Search, Vorlesung SS 2020, 29.05.2020

Chapter: Escaping Local Minima. I. Simulated Annealing, Vorlesung SS 2020, 17.05.2020

Chapter: Representation, Vorlesung SS 2020, 17.05.2020

Chapter 1: Problem Solving and Basic Concepts. II. Basic Concepts, Vorlesung SS 2020, 16.05.2020

Chapter 1: Problem Solving and Basic Concepts. I. Problem Solving, Vorlesung SS 2020, 15.05.2020

Chapter 0: Nature-inspired optimization methods, Vorlesung SS 2020, 03.05.2020