Multi-objective optimization, 

Автор: Fran S?rgio Lobato; Valder Steffen Jr.
Название: Multi-Objective Optimization Problems
ISBN: 3319585649 ISBN-13(EAN): 9783319585642
Издательство: Springer
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Цена: 46570.00 T
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Описание: The methodology is applied to solve mathematical functions considering test cases from the literature and various engineering systems design, such as cantilevered beam design, biochemical reactor, crystallization process, machine tool spindle design, rotary dryer design, among others.

Автор: Maschler
Название: Game Theory
ISBN: 1107005485 ISBN-13(EAN): 9781107005488
Издательство: Cambridge Academ
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Цена: 69690.00 T
Наличие на складе: Невозможна поставка.
Описание: Covering both noncooperative and cooperative games, this comprehensive introduction to game theory also includes some advanced chapters on auctions, games with incomplete information, games with vector payoffs, stable matchings and the bargaining set. Mathematically oriented, the book presents every theorem alongside a proof. The material is presented clearly and every concept is illustrated with concrete examples from a broad range of disciplines. With numerous exercises the book is a thorough and extensive guide to game theory from undergraduate through graduate courses in economics, mathematics, computer science, engineering and life sciences to being an authoritative reference for researchers.

Автор: Bechikh
Название: Recent Advances in Evolutionary Multi-objective Optimization
ISBN: 3319429779 ISBN-13(EAN): 9783319429779
Издательство: Springer
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Цена: 111790.00 T
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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.

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: 130430.00 T
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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.

Автор: Panos M. Pardalos; Antanas ?ilinskas; Julius ?ilin
Название: Non-Convex Multi-Objective Optimization
ISBN: 3319610058 ISBN-13(EAN): 9783319610054
Издательство: Springer
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Цена: 83850.00 T
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Описание: Recent results on non-convex multi-objective optimization problems and methods are presented in this book, with particular attention to expensive black-box objective functions.

Автор: Chi-Keong Goh; Kay Chen Tan
Название: Evolutionary Multi-objective Optimization in Uncertain Environments
ISBN: 3642101135 ISBN-13(EAN): 9783642101137
Издательство: Springer
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Цена: 139750.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
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.

Автор: Carpentier Pierre
Название: Stochastic Multi-Stage Optimization
ISBN: 3319181378 ISBN-13(EAN): 9783319181370
Издательство: Springer
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Цена: 88500.00 T
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Описание: The focus of the present volume is stochastic optimization of dynamical systems in discrete time where - by concentrating on the role of information regarding optimization problems - it discusses the related discretization issues.

Автор: Minghui Zhu; Sonia Mart?nez
Название: Distributed Optimization-Based Control of Multi-Agent Networks in Complex Environments
ISBN: 3319190717 ISBN-13(EAN): 9783319190716
Издательство: Springer
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Цена: 46570.00 T
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Описание: With the goal of alleviating the paucity of knowledge about advanced dementia, and helping to improve the care and services that are increasingly needed for the growing numbers of people living with dementia-type diseases, this book provides evidence-based measurement scales for use by researchers and care providers who are seeking to improve our understanding of the final stages of this disease.

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: 95770.00 T
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.

Автор: Jyotsna K. Mandal; Somnath Mukhopadhyay; Paramarth
Название: Multi-Objective Optimization
ISBN: 9811346399 ISBN-13(EAN): 9789811346392
Издательство: Springer
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Цена: 149060.00 T
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Описание: This book brings together the latest findings on efficient solutions of multi/many-objective optimization problems from the leading researchers in the field. The focus is on solving real-world optimization problems using strategies ranging from evolutionary to hybrid frameworks, and involving various computation platforms. The topics covered include solution frameworks using evolutionary to hybrid models in application areas like Analytics, Cancer Research, Traffic Management, Networks and Communications, E-Governance, Quantum Technology, Image Processing, etc. As such, the book offers a valuable resource for all postgraduate students and researchers interested in exploring solution frameworks for multi/many-objective optimization problems.

Автор: Seyedali Mirjalili; Jin Song Dong
Название: Multi-Objective Optimization using Artificial Intelligence Techniques
ISBN: 3030248348 ISBN-13(EAN): 9783030248345
Издательство: Springer
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Цена: 55890.00 T
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Описание: This book focuses on the most well-regarded and recent nature-inspired algorithms capable of solving optimization problems with multiple objectives. Firstly, it provides preliminaries and essential definitions in multi-objective problems and different paradigms to solve them. It then presents an in-depth explanations of the theory, literature review, and applications of several widely-used algorithms, such as Multi-objective Particle Swarm Optimizer, Multi-Objective Genetic Algorithm and Multi-objective GreyWolf Optimizer Due to the simplicity of the techniques and flexibility, readers from any field of study can employ them for solving multi-objective optimization problem. The book provides the source codes for all the proposed algorithms on a dedicated webpage.

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: 97820.00 T
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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.