Recent Advances In Evolutionary Multi Objective Optimization
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Recent Advances In Evolutionary Multi Objective Optimization
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Author : Slim Bechikh
language : en
Publisher: Springer
Release Date : 2016-08-09
Recent Advances In Evolutionary Multi Objective Optimization written by Slim Bechikh and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-09 with Technology & Engineering categories.
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.
Evolutionary Multiobjective Optimization
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Author : Ajith Abraham
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-04-22
Evolutionary Multiobjective Optimization written by Ajith Abraham 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 2005-04-22 with Computers categories.
Evolutionary Multiobjective Optimization is a rare collection of the latest state-of-the-art theoretical research, design challenges and applications in the field of multiobjective optimization paradigms using evolutionary algorithms. It includes two introductory chapters giving all the fundamental definitions, several complex test functions and a practical problem involving the multiobjective optimization of space structures under static and seismic loading conditions used to illustrate the various multiobjective optimization concepts. Important features include: Detailed overview of all the multiobjective optimization paradigms using evolutionary algorithms Excellent coverage of timely, advanced multiobjective optimization topics State-of-the-art theoretical research and application developments Chapters authored by pioneers in the field Academics and industrial scientists as well as engineers engaged in research, development and application of evolutionary algorithm based Multiobjective Optimization will find the comprehensive coverage of this book invaluable.
Evolutionary Algorithms For Solving Multi Objective Problems
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Author : Carlos Coello Coello
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-09-18
Evolutionary Algorithms For Solving Multi Objective Problems written by Carlos Coello Coello 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 2007-09-18 with Computers categories.
This textbook is a second edition of Evolutionary Algorithms for Solving Multi-Objective Problems, significantly expanded and adapted for the classroom. The various features of multi-objective evolutionary algorithms are presented here in an innovative and student-friendly fashion, incorporating state-of-the-art research. The book disseminates the application of evolutionary algorithm techniques to a variety of practical problems. It contains exhaustive appendices, index and bibliography and links to a complete set of teaching tutorials, exercises and solutions.
Recent Advances In Simulated Evolution And Learning
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Author : K. C. Tan
language : en
Publisher: World Scientific
Release Date : 2004
Recent Advances In Simulated Evolution And Learning written by K. C. Tan and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Computers categories.
Inspired by the Darwinian framework of evolution through natural selection and adaptation, the field of evolutionary computation has been growing very rapidly, and is today involved in many diverse application areas. This book covers the latest advances in the theories, algorithms, and applications of simulated evolution and learning techniques. It provides insights into different evolutionary computation techniques and their applications in domains such as scheduling, control and power, robotics, signal processing, and bioinformatics. The book will be of significant value to all postgraduates, research scientists and practitioners dealing with evolutionary computation or complex real-world problems. This book has been selected for coverage in: . OCo Index to Scientific & Technical Proceedings (ISTP CDROM version / ISI Proceedings). OCo CC Proceedings OCo Engineering & Physical Sciences. Sample Chapter(s). Chapter 1: Co-Evolutionary Learning in Strategic Environments (231 KB). Contents: Evolutionary Theory: Using Evolution to Learn User Preferences (S Ujjin & P J Bentley); Evolutionary Learning Strategies for Artificial Life Characters (M L Netto et al.); The Influence of Stochastic Quality Functions on Evolutionary Search (B Sendhoff et al.); A Real-Coded Cellular Genetic Algorithm Inspired by PredatorOCoPrey Interactions (X Li & S Sutherland); Automatic Modularization with Speciated Neural Network Ensemble (V R Khare & X Yao); Evolutionary Applications: Image Classification using Particle Swarm Optimization (M G Omran et al.); Evolution of Fuzzy Rule Based Controllers for Dynamic Environments (J Riley & V Ciesielski); A Genetic Algorithm for Joint Optimization of Spare Capacity and Delay in Self-Healing Network (S Kwong & H W Chong); Joint Attention in the Mimetic Context OCo What is a OC Mimetic SameOCO? (T Shiose et al.); Time Series Forecast with Elman Neural Networks and Genetic Algorithms (L X Xu et al.); and other articles. Readership: Upper level undergraduates, graduate students, academics, researchers and industrialists in artificial intelligence, evolutionary computation, fuzzy logic and neural networks."
Evolutionary Large Scale Multi Objective Optimization And Applications
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Author : Xingyi Zhang
language : en
Publisher: John Wiley & Sons
Release Date : 2024-09-11
Evolutionary Large Scale Multi Objective Optimization And Applications written by Xingyi Zhang and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-11 with Technology & Engineering categories.
Tackle the most challenging problems in science and engineering with these cutting-edge algorithms Multi-objective optimization problems (MOPs) are those in which more than one objective needs to be optimized simultaneously. As a ubiquitous component of research and engineering projects, these problems are notoriously challenging. In recent years, evolutionary algorithms (EAs) have shown significant promise in their ability to solve MOPs, but challenges remain at the level of large-scale multi-objective optimization problems (LSMOPs), where the number of variables increases and the optimized solution is correspondingly harder to reach. Evolutionary Large-Scale Multi-Objective Optimization and Applications constitutes a systematic overview of EAs and their capacity to tackle LSMOPs. It offers an introduction to both the problem class and the algorithms before delving into some of the cutting-edge algorithms which have been specifically adapted to solving LSMOPs. Deeply engaged with specific applications and alert to the latest developments in the field, it’s a must-read for students and researchers facing these famously complex but crucial optimization problems. The book’s readers will also find: Analysis of multi-optimization problems in fields such as machine learning, network science, vehicle routing, and more Discussion of benchmark problems and performance indicators for LSMOPs Presentation of a new taxonomy of algorithms in the field Evolutionary Large-Scale Multi-Objective Optimization and Applications is ideal for advanced students, researchers, and scientists and engineers facing complex optimization problems.
The Routledge Companion To Artificial Intelligence In Architecture
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Author : Imdat As
language : en
Publisher: Routledge
Release Date : 2021-05-05
The Routledge Companion To Artificial Intelligence In Architecture written by Imdat As and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-05 with Architecture categories.
Providing the most comprehensive source available, this book surveys the state of the art in artificial intelligence (AI) as it relates to architecture. This book is organized in four parts: theoretical foundations, tools and techniques, AI in research, and AI in architectural practice. It provides a framework for the issues surrounding AI and offers a variety of perspectives. It contains 24 consistently illustrated contributions examining seminal work on AI from around the world, including the United States, Europe, and Asia. It articulates current theoretical and practical methods, offers critical views on tools and techniques, and suggests future directions for meaningful uses of AI technology. Architects and educators who are concerned with the advent of AI and its ramifications for the design industry will find this book an essential reference.
Evolutionary Multi Objective Optimization In Uncertain Environments
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Author : Chi-Keong Goh
language : en
Publisher: Springer
Release Date : 2009-02-03
Evolutionary Multi Objective Optimization In Uncertain Environments written by Chi-Keong Goh and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-02-03 with Computers categories.
Evolutionary algorithms are sophisticated search methods that have been found to be very efficient and effective in solving complex real-world multi-objective problems where conventional optimization tools fail to work well. Despite the tremendous amount of work done in the development of these algorithms in the past decade, many researchers assume that the optimization problems are deterministic and uncertainties are rarely examined. 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. In this book, we hope to expose the readers to a range of optimization issues and concepts, and to encourage a greater degree of appreciation of evolutionary computation techniques and the exploration of new ideas that can better handle uncertainties. "Evolutionary Multi-Objective Optimization in Uncertain Environments: Issues and Algorithms" is intended for a wide readership and will be a valuable reference for engineers, researchers, senior undergraduates and graduate students who are interested in the areas of evolutionary multi-objective optimization and uncertainties.
Recent Advances On Hybrid Approaches For Designing Intelligent Systems
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Author : Oscar Castillo
language : en
Publisher: Springer
Release Date : 2014-03-26
Recent Advances On Hybrid Approaches For Designing Intelligent Systems written by Oscar Castillo and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-03-26 with Technology & Engineering categories.
This book describes recent advances on hybrid intelligent systems using soft computing techniques for diverse areas of application, such as intelligent control and robotics, pattern recognition, time series prediction and optimization complex problems. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks and bio-inspired optimization algorithms, which can be used to produce powerful hybrid intelligent systems. The book is organized in five main parts, which contain a group of papers around a similar subject. The first part consists of papers with the main theme of type-2 fuzzy logic, which basically consists of papers that propose new models and applications for type-2 fuzzy systems. The second part contains papers with the main theme of bio-inspired optimization algorithms, which are basically papers using nature-inspired techniques to achieve optimization of complex optimization problems in diverse areas of application. The third part contains papers that deal with new models and applications of neural networks in real world problems. The fourth part contains papers with the theme of intelligent optimization methods, which basically consider the proposal of new methods of optimization to solve complex real world optimization problems. The fifth part contains papers with the theme of evolutionary methods and intelligent computing, which are papers considering soft computing methods for applications related to diverse areas, such as natural language processing, recommending systems and optimization.
Controller Tuning With Evolutionary Multiobjective Optimization
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Author : Gilberto Reynoso Meza
language : en
Publisher: Springer
Release Date : 2016-11-04
Controller Tuning With Evolutionary Multiobjective Optimization written by Gilberto Reynoso Meza and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-04 with Technology & Engineering categories.
This book is devoted to Multiobjective Optimization Design (MOOD) procedures for controller tuning applications, by means of Evolutionary Multiobjective Optimization (EMO). It presents developments in tools, procedures and guidelines to facilitate this process, covering the three fundamental steps in the procedure: problem definition, optimization and decision-making. The book is divided into four parts. The first part, Fundamentals, focuses on the necessary theoretical background and provides specific tools for practitioners. The second part, Basics, examines a range of basic examples regarding the MOOD procedure for controller tuning, while the third part, Benchmarking, demonstrates how the MOOD procedure can be employed in several control engineering problems. The fourth part, Applications, is dedicated to implementing the MOOD procedure for controller tuning in real processes.
Adaptive Formation Of Pareto Front In Evolutionary Multi Objective Optimization
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Author : Ozer Ciftcioglu
language : en
Publisher:
Release Date : 2009
Adaptive Formation Of Pareto Front In Evolutionary Multi Objective Optimization written by Ozer Ciftcioglu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with categories.
A novel adaptive approach for formation of the Pareto front in multi-objective optimization is presented. The approach is an adaptive stochastic search, where a relaxed dominance concept is introduced, and the relaxation angle is adapted during the search. This approach is a dual counterpart of gradient-based stochastic adaptive algorithms. In this duality the fitnessfunction is the dual of stochastic gradient, and the degree of relaxation is the dual of the step-size parameter. The adaptation is found to be significantly favorable for.