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Computational Intelligence In Optimization


Computational Intelligence In Optimization
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Computational Intelligence In Optimization


Computational Intelligence In Optimization
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Author : Yoel Tenne
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-06-30

Computational Intelligence In Optimization written by Yoel Tenne and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-06-30 with Technology & Engineering categories.


This collection of recent studies spans a range of computational intelligence applications, emphasizing their application to challenging real-world problems. Covers Intelligent agent-based algorithms, Hybrid intelligent systems, Machine learning and more.



Computational Intelligence For Optimization


Computational Intelligence For Optimization
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Author : Nirwan Ansari
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Computational Intelligence For Optimization written by Nirwan Ansari and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.


The field of optimization is interdisciplinary in nature, and has been making a significant impact on many disciplines. As a result, it is an indispensable tool for many practitioners in various fields. Conventional optimization techniques have been well established and widely published in many excellent textbooks. However, there are new techniques, such as neural networks, simulated anneal ing, stochastic machines, mean field theory, and genetic algorithms, which have been proven to be effective in solving global optimization problems. This book is intended to provide a technical description on the state-of-the-art development in advanced optimization techniques, specifically heuristic search, neural networks, simulated annealing, stochastic machines, mean field theory, and genetic algorithms, with emphasis on mathematical theory, implementa tion, and practical applications. The text is suitable for a first-year graduate course in electrical and computer engineering, computer science, and opera tional research programs. It may also be used as a reference for practicing engineers, scientists, operational researchers, and other specialists. This book is an outgrowth of a couple of special topic courses that we have been teaching for the past five years. In addition, it includes many results from our inter disciplinary research on the topic. The aforementioned advanced optimization techniques have received increasing attention over the last decade, but relatively few books have been produced.



Intelligent Computational Optimization In Engineering


Intelligent Computational Optimization In Engineering
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Author : Mario Köppen
language : en
Publisher: Springer
Release Date : 2011-07-15

Intelligent Computational Optimization In Engineering written by Mario Köppen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-07-15 with Technology & Engineering categories.


We often come across computational optimization virtually in all branches of engineering and industry. Many engineering problems involve heuristic search and optimization, and, once discretized, may become combinatorial in nature, which gives rise to certain difficulties in terms of solution procedure. Some of these problems have enormous search spaces, are NP-hard and hence require heuristic solution techniques. Another difficulty is the lack of ability of classical solution techniques to determine appropriate optima of non-convex problems. Under these conditions, recent advances in computational optimization techniques have been shown to be advantageous and successful compared to classical approaches. This Volume presents some of the latest developments with a focus on the design of algorithms for computational optimization and their applications in practice. Through the chapters of this book, researchers and practitioners share their experience and newest methodologies with regard to intelligent optimization and provide various case studies of the application of intelligent optimization techniques in real-world applications.This book can serve as an excellent reference for researchers and graduate students in computer science, various engineering disciplines and the industry.



Computational Intelligence And Optimization Methods For Control Engineering


Computational Intelligence And Optimization Methods For Control Engineering
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Author : Maude Josée Blondin
language : en
Publisher: Springer Nature
Release Date : 2019-09-20

Computational Intelligence And Optimization Methods For Control Engineering written by Maude Josée Blondin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-20 with Mathematics categories.


This volume presents some recent and principal developments related to computational intelligence and optimization methods in control. Theoretical aspects and practical applications of control engineering are covered by 14 self-contained contributions. Additional gems include the discussion of future directions and research perspectives designed to add to the reader’s understanding of both the challenges faced in control engineering and the insights into the developing of new techniques. With the knowledge obtained, readers are encouraged to determine the appropriate control method for specific applications.



Computational Intelligence Optimization And Inverse Problems With Applications In Engineering


Computational Intelligence Optimization And Inverse Problems With Applications In Engineering
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Author : Gustavo Mendes Platt
language : en
Publisher: Springer
Release Date : 2018-09-25

Computational Intelligence Optimization And Inverse Problems With Applications In Engineering written by Gustavo Mendes Platt and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-25 with Technology & Engineering categories.


This book focuses on metaheuristic methods and its applications to real-world problems in Engineering. The first part describes some key metaheuristic methods, such as Bat Algorithms, Particle Swarm Optimization, Differential Evolution, and Particle Collision Algorithms. Improved versions of these methods and strategies for parameter tuning are also presented, both of which are essential for the practical use of these important computational tools. The second part then applies metaheuristics to problems, mainly in Civil, Mechanical, Chemical, Electrical, and Nuclear Engineering. Other methods, such as the Flower Pollination Algorithm, Symbiotic Organisms Search, Cross-Entropy Algorithm, Artificial Bee Colonies, Population-Based Incremental Learning, Cuckoo Search, and Genetic Algorithms, are also presented. The book is rounded out by recently developed strategies, or hybrid improved versions of existing methods, such as the Lightning Optimization Algorithm, Differential Evolution with Particle Collisions, and Ant Colony Optimization with Dispersion – state-of-the-art approaches for the application of computational intelligence to engineering problems. The wide variety of methods and applications, as well as the original results to problems of practical engineering interest, represent the primary differentiation and distinctive quality of this book. Furthermore, it gathers contributions by authors from four countries – some of which are the original proponents of the methods presented – and 18 research centers around the globe.



Multi Objective Optimization In Computational Intelligence Theory And Practice


Multi Objective Optimization In Computational Intelligence Theory And Practice
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Author : Thu Bui, Lam
language : en
Publisher: IGI Global
Release Date : 2008-05-31

Multi Objective Optimization In Computational Intelligence Theory And Practice written by Thu Bui, Lam and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-05-31 with Technology & Engineering categories.


Multi-objective optimization (MO) is a fast-developing field in computational intelligence research. Giving decision makers more options to choose from using some post-analysis preference information, there are a number of competitive MO techniques with an increasingly large number of MO real-world applications. Multi-Objective Optimization in Computational Intelligence: Theory and Practice explores the theoretical, as well as empirical, performance of MOs on a wide range of optimization issues including combinatorial, real-valued, dynamic, and noisy problems. This book provides scholars, academics, and practitioners with a fundamental, comprehensive collection of research on multi-objective optimization techniques, applications, and practices.



Foundations Of Computational Intelligence Volume 3


Foundations Of Computational Intelligence Volume 3
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Author : Ajith Abraham
language : en
Publisher: Springer
Release Date : 2009-05-01

Foundations Of Computational Intelligence Volume 3 written by Ajith Abraham and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-05-01 with Computers categories.


Global optimization is a branch of applied mathematics and numerical analysis that deals with the task of finding the absolutely best set of admissible conditions to satisfy certain criteria / objective function(s), formulated in mathematical terms. Global optimization includes nonlinear, stochastic and combinatorial programming, multiobjective programming, control, games, geometry, approximation, algorithms for parallel architectures and so on. Due to its wide usage and applications, it has gained the attention of researchers and practitioners from a plethora of scientific domains. Typical practical examples of global optimization applications include: Traveling salesman problem and electrical circuit design (minimize the path length); safety engineering (building and mechanical structures); mathematical problems (Kepler conjecture); Protein structure prediction (minimize the energy function) etc. Global Optimization algorithms may be categorized into several types: Deterministic (example: branch and bound methods), Stochastic optimization (example: simulated annealing). Heuristics and meta-heuristics (example: evolutionary algorithms) etc. Recently there has been a growing interest in combining global and local search strategies to solve more complicated optimization problems. This edited volume comprises 17 chapters, including several overview Chapters, which provides an up-to-date and state-of-the art research covering the theory and algorithms of global optimization. Besides research articles and expository papers on theory and algorithms of global optimization, papers on numerical experiments and on real world applications were also encouraged. The book is divided into 2 main parts.



Multi Objective Optimization Using Artificial Intelligence Techniques


Multi Objective Optimization Using Artificial Intelligence Techniques
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Author : Seyedali Mirjalili
language : en
Publisher: Springer
Release Date : 2019-07-24

Multi Objective Optimization Using Artificial Intelligence Techniques written by Seyedali Mirjalili and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-24 with Technology & Engineering categories.


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.



Computational Intelligence In Expensive Optimization Problems


Computational Intelligence In Expensive Optimization Problems
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Author : Yoel Tenne
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-03-10

Computational Intelligence In Expensive Optimization Problems written by Yoel Tenne and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-03-10 with Technology & Engineering categories.


In modern science and engineering, laboratory experiments are replaced by high fidelity and computationally expensive simulations. Using such simulations reduces costs and shortens development times but introduces new challenges to design optimization process. Examples of such challenges include limited computational resource for simulation runs, complicated response surface of the simulation inputs-outputs, and etc. Under such difficulties, classical optimization and analysis methods may perform poorly. This motivates the application of computational intelligence methods such as evolutionary algorithms, neural networks and fuzzy logic, which often perform well in such settings. This is the first book to introduce the emerging field of computational intelligence in expensive optimization problems. Topics covered include: dedicated implementations of evolutionary algorithms, neural networks and fuzzy logic. reduction of expensive evaluations (modelling, variable-fidelity, fitness inheritance), frameworks for optimization (model management, complexity control, model selection), parallelization of algorithms (implementation issues on clusters, grids, parallel machines), incorporation of expert systems and human-system interface, single and multiobjective algorithms, data mining and statistical analysis, analysis of real-world cases (such as multidisciplinary design optimization). The edited book provides both theoretical treatments and real-world insights gained by experience, all contributed by leading researchers in the respective fields. As such, it is a comprehensive reference for researchers, practitioners, and advanced-level students interested in both the theory and practice of using computational intelligence for expensive optimization problems.



Innovative Computational Intelligence A Rough Guide To 134 Clever Algorithms


Innovative Computational Intelligence A Rough Guide To 134 Clever Algorithms
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Author : Bo Xing
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-12-13

Innovative Computational Intelligence A Rough Guide To 134 Clever Algorithms written by Bo Xing and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-13 with Technology & Engineering categories.


The first notable feature of this book is its innovation: Computational intelligence (CI), a fast evolving area, is currently attracting lots of researchers’ attention in dealing with many complex problems. At present, there are quite a lot competing books existing in the market. Nevertheless, the present book is markedly different from the existing books in that it presents new paradigms of CI that have rarely mentioned before, as opposed to the traditional CI techniques or methodologies employed in other books. During the past decade, a number of new CI algorithms are proposed. Unfortunately, they spread in a number of unrelated publishing directions which may hamper the use of such published resources. These provide us with motivation to analyze the existing research for categorizing and synthesizing it in a meaningful manner. The mission of this book is really important since those algorithms are going to be a new revolution in computer science. We hope it will stimulate the readers to make novel contributions or even start a new paradigm based on nature phenomena. Although structured as a textbook, the book's straightforward, self-contained style will also appeal to a wide audience of professionals, researchers and independent learners. We believe that the book will be instrumental in initiating an integrated approach to complex problems by allowing cross-fertilization of design principles from different design philosophies. The second feature of this book is its comprehensiveness: Through an extensive literature research, there are 134 innovative CI algorithms covered in this book.