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Evolutionary Multi-objective Optimization in Uncertain Environments, Chi-Keong Goh; Kay Chen Tan


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Автор: Chi-Keong Goh; Kay Chen Tan
Название:  Evolutionary Multi-objective Optimization in Uncertain Environments
ISBN: 9783642101137
Издательство: Springer
Классификация:

ISBN-10: 3642101135
Обложка/Формат: Paperback
Страницы: 271
Вес: 0.40 кг.
Дата издания: 28.10.2010
Серия: Studies in Computational Intelligence
Язык: English
Размер: 234 x 156 x 15
Основная тема: Computer Science
Подзаголовок: Issues and Algorithms
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: The primary motivation of this book is to provide a comprehensive introduction on the design and application of evolutionary algorithms for multi-objective optimization in the presence of uncertainties. The book is intended for a wide readership.


Evolutionary Multi-Criterion Optimization

Автор: Carlos M. Fonseca; Xavier Gandibleux; Jin-Kao Hao;
Название: Evolutionary Multi-Criterion Optimization
ISBN: 3642010199 ISBN-13(EAN): 9783642010194
Издательство: Springer
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Цена: 14673.00 р.
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Описание: Constitutes the refereed proceedings of the 5th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2009, held in Nantes, France in April 2009. This book presents 39 revised full papers together with 5 invited talks that were reviewed and selected from 72 submissions.

Recent Advances in Evolutionary Multi-objective Optimization

Автор: Bechikh
Название: Recent Advances in Evolutionary Multi-objective Optimization
ISBN: 3319429779 ISBN-13(EAN): 9783319429779
Издательство: Springer
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Цена: 16769.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book covers the most recent advances in the field of evolutionary multiobjective optimization. With the aim of drawing the attention of up-and coming scientists towards exciting prospects at the forefront of computational intelligence, the authors have made an effort to ensure that the ideas conveyed herein are accessible to the widest audience. The book begins with a summary of the basic concepts in multi-objective optimization. This is followed by brief discussions on various algorithms that have been proposed over the years for solving such problems, ranging from classical (mathematical) approaches to sophisticated evolutionary ones that are capable of seamlessly tackling practical challenges such as non-convexity, multi-modality, the presence of multiple constraints, etc. Thereafter, some of the key emerging aspects that are likely to shape future research directions in the field are presented. These include: optimization in dynamic environments, multi-objective bilevel programming, handling high dimensionality under many objectives, and evolutionary multitasking. In addition to theory and methodology, this book describes several real-world applications from various domains, which will expose the readers to the versatility of evolutionary multi-objective optimization.

Application of Evolutionary Algorithms for Multi-objective Optimization in VLSI and Embedded Systems

Автор: M.C. Bhuvaneswari
Название: Application of Evolutionary Algorithms for Multi-objective Optimization in VLSI and Embedded Systems
ISBN: 8132219570 ISBN-13(EAN): 9788132219576
Издательство: Springer
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Цена: 19564.00 р.
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Описание: This book describes how evolutionary algorithms (EA), including genetic algorithms (GA) and particle swarm optimization (PSO) can be utilized for solving multi-objective optimization problems in the area of embedded and VLSI system design.

Application of Evolutionary Algorithms for Multi-objective Optimization in VLSI and Embedded Systems

Автор: M.C. Bhuvaneswari
Название: Application of Evolutionary Algorithms for Multi-objective Optimization in VLSI and Embedded Systems
ISBN: 8132235398 ISBN-13(EAN): 9788132235392
Издательство: Springer
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Цена: 14365.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book describes how evolutionary algorithms (EA), including genetic algorithms (GA) and particle swarm optimization (PSO) can be utilized for solving multi-objective optimization problems in the area of embedded and VLSI system design.

Evolutionary Computation in Dynamic and Uncertain Environments

Автор: Shengxiang Yang; Yew-Soon Ong; Yaochu Jin
Название: Evolutionary Computation in Dynamic and Uncertain Environments
ISBN: 3642080650 ISBN-13(EAN): 9783642080654
Издательство: Springer
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Цена: 36570.00 р.
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Описание: Discussion includes representative methods for addressing major sources of uncertainties in evolutionary computation, including handle of noisy fitness functions, use of approximate fitness functions, search for robust solutions, and tracking moving optimums.

Evolutionary Multi-Criterion Optimization

Автор: Heike Trautmann; G?nter Rudolph; Kathrin Klamroth;
Название: Evolutionary Multi-Criterion Optimization
ISBN: 3319541560 ISBN-13(EAN): 9783319541563
Издательство: Springer
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Цена: 13974.00 р.
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Описание: This book constitutes the refereed proceedings of the 9th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2017 held in Munster, Germany in March 2017. The EMO 2017 aims to discuss all aspects of EMO development and deployment, including theoretical foundations; parallel EMO models; EMO algorithm implementations.

Evolutionary Multi-Criterion Optimization

Автор: Ant?nio Gaspar-Cunha; Carlos Henggeler Antunes; Ca
Название: Evolutionary Multi-Criterion Optimization
ISBN: 3319158910 ISBN-13(EAN): 9783319158914
Издательство: Springer
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Цена: 12298.00 р.
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Описание: This book constitutes the refereed proceedings of the 8th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2015 held in Guimaraes, Portugal in March/April 2015.

Evolutionary Multi-Criterion Optimization

Автор: Ant?nio Gaspar-Cunha; Carlos Henggeler Antunes; Ca
Название: Evolutionary Multi-Criterion Optimization
ISBN: 331915933X ISBN-13(EAN): 9783319159331
Издательство: Springer
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Цена: 8944.00 р.
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Описание: This book constitutes the refereed proceedings of the 8th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2015 held in Guimaraes, Portugal in March/April 2015.

Evolutionary Algorithms for Solving Multi-Objective Problems

Автор: Carlos Coello Coello; Gary B. Lamont; David A. van
Название: Evolutionary Algorithms for Solving Multi-Objective Problems
ISBN: 1489994602 ISBN-13(EAN): 9781489994608
Издательство: Springer
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Цена: 13974.00 р.
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Описание: This textbook is a second edition of Evolutionary Algorithms for Solving Multi-Objective Problems, significantly expanded and adapted for the classroom. It provides links to a complete set of teaching tutorials, exercises and solutions.

Constraint-Handling in Evolutionary Optimization

Автор: Efr?n Mezura-Montes
Название: Constraint-Handling in Evolutionary Optimization
ISBN: 3642101550 ISBN-13(EAN): 9783642101557
Издательство: Springer
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Цена: 20962.00 р.
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Описание: This book is the result of a special session on constraint-handling techniques used in evolutionary algorithms within the Congress on Evolutionary Computation (CEC) in 2007. It presents recent research in constraint-handling in evolutionary optimization.

Analog Circuits and Systems Optimization based on Evolutionary Computation Techniques

Автор: Manuel Barros; Jorge Guilherme; Nuno Horta
Название: Analog Circuits and Systems Optimization based on Evolutionary Computation Techniques
ISBN: 3642123457 ISBN-13(EAN): 9783642123450
Издательство: Springer
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Цена: 23757.00 р.
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Описание: Transistor-level design for complex mixed-signal systems-on-chip remains difficult to automate. This book shows how a modified genetic algorithm kernel can improve efficiency in the analog IC design cycle and includes a worked example of the method.

Analog Circuits and Systems Optimization based on Evolutionary Computation Techniques

Автор: Manuel Barros; Jorge Guilherme; Nuno Horta
Название: Analog Circuits and Systems Optimization based on Evolutionary Computation Techniques
ISBN: 3642263232 ISBN-13(EAN): 9783642263231
Издательство: Springer
Рейтинг:
Цена: 23757.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Transistor-level design for complex mixed-signal systems-on-chip remains difficult to automate. This book shows how a modified genetic algorithm kernel can improve efficiency in the analog IC design cycle and includes a worked example of the method.


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