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Introduction to Global Optimization

Abstract : These slides constitute a 12h introductory course on global optimization. The course starts with basic concepts specific to global optimization and different from those underlying local optimization algorithms. A selection of 6 algorithms is then presented: random search, randomly restarted local searches, simulated annealing, CMA-ES and Bayesian Optimization. This selection is meant to cover the main mechanisms behind global searches. Pre-requisites are: linear algebra, basic probabilities and local optimization (gradient methods, necessary optimality conditions).
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Contributor : Le Riche Rodolphe Connect in order to contact the contributor
Submitted on : Wednesday, December 22, 2021 - 2:27:47 PM
Last modification on : Thursday, January 13, 2022 - 5:00:03 AM


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  • HAL Id : hal-03500652, version 1


Rodolphe Le Riche, Charlie Sire. Introduction to Global Optimization. Master. France. 2021. ⟨hal-03500652v1⟩



Les métriques sont temporairement indisponibles