Оптимизация физических практикумов Николай Вал. Калачев und Сергей Мих. Кокин

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Supported by a website featuring solutions to exercises, further examples and computer code for numerical examples. Treats the experimental techniques and instrumentation often used in nuclear and particle physics experiments as well as in various other experiments. This book provides useful results and formulae, technical know-how and informative details. It is intended for graduate students, scientists, engineers, and technical assistants. This volume presents a selection of studies that address a substantial list of key challenges arising in space engineering.

The contributing authors are well-recognized researchers and practitioners in space engineering and in applied optimization. Novel points of view such as computational global optimization, multidisciplinary design optimization and optimal control theory are emphasized and both mathematical modeling and algorithmic aspects are discussed.

Classic space application problems, such as trajectory optimization, are presented together with systems engineering and logistics aspects, such as propulsion system design and cargo accommodation. A particular attention is paid to the scenarios expected for future interplanetary explorations. Modeling and Optimization in Space Engineering will benefit researchers and practitioners in the field of space engineering, as well as aerospace graduate and post-graduate students willing to broaden their academic knowledge, by studying real-world applications and challenging problems that they will be likely to tackle in their future professional activities.

This book offers an in-depth overview of polyhedral methods and efficient algorithms in combinatorial optimization. These methods form a broad, coherent and powerful kernel in combinatorial optimization, with strong links to discrete mathematics, mathematical programming and computer science.

In eight parts, various areas are treated, each starting with an elementary introduction to the area, with short, elegant proofs of the principal results, and each evolving to the more advanced methods and results, with full proofs of some of the deepest theorems in the area.

Over references to further research are given, and historical surveys on the basic subjects are presented. Robust Optimization is a method to improve robustness using low-cost variations of a single, conceptual design. The benefits of Robust Optimization include faster product development cycles; faster launch cycles; fewer manufacturing problems; fewer fiel. ООО "Логосфера " Тел: Книга будет полезна преподавателям, аспирантам и студентам - будущим физикам, инженерам и технологам.

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