Druck auf Anfrage Neuware - Printed after ordering - Mathematical optimization techniques are among the most successful tools for controlling technical systems optimally with feasibility guarantees. Yet, they are often centralized-all data has to be collected in one central and computationally powerful entity. Methods from distributed optimization overcome this limitation. Classical approaches, however, are often not applicable due to non-convexities. This work develops one of the first frameworks for distributed non-convex optimization.

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Bibliographic Details

Title: Distributed Optimization with Application to Power Systems and Control
Publisher: Karlsruher Institut F�r Technologie
Publication Date: 2022
Language: English
ISBN 10: 3731511800
ISBN 13: 9783731511809
Binding: Taschenbuch
Condition: Neu
Dimensions: 210 millimeters width by 148 millimeters height by 15 millimeters depth
Weight: 334 grams

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Mathematical optimization techniques are among the most successful tools for controlling technical systems optimally with feasibility guarantees. Yet, they are often centralized—all data has to be collected in one central and computationally powerful entity. Methods from distributed optimization overcome this limitation. Classical approaches, however, are often not applicable due to non-convexities. This work develops one of the first frameworks for distributed non-convex optimization.

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