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Multi Objective Optimization In Computational Intelligence

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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 Computers 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.

Multi Objective Optimization In Computational Intelligence

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Author : Lam Thu Bui
language : en
Publisher: IGI Global Snippet
Release Date : 2008

Multi Objective Optimization In Computational Intelligence written by Lam Thu Bui and has been published by IGI Global Snippet this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Mathematics 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.

Advances In Multi Objective Nature Inspired Computing

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Author : Carlos Coello Coello
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-02-04

Advances In Multi Objective Nature Inspired Computing 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 2010-02-04 with Mathematics categories.

The purpose of this book is to collect contributions that deal with the use of nature inspired metaheuristics for solving multi-objective combinatorial optimization problems. Such a collection intends to provide an overview of the state-of-the-art developments in this field, with the aim of motivating more researchers in operations research, engineering, and computer science, to do research in this area. As such, this book is expected to become a valuable reference for those wishing to do research on the use of nature inspired metaheuristics for solving multi-objective combinatorial optimization problems.

Multi Objective Swarm Intelligence

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Author : Satchidananda Dehuri
language : en
Publisher: Springer
Release Date : 2015-03-10

Multi Objective Swarm Intelligence written by Satchidananda Dehuri and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-10 with Technology & Engineering categories.

The aim of this book is to understand the state-of-the-art theoretical and practical advances of swarm intelligence. It comprises seven contemporary relevant chapters. In chapter 1, a review of Bacteria Foraging Optimization (BFO) techniques for both single and multiple criterions problem is presented. A survey on swarm intelligence for multiple and many objectives optimization is presented in chapter 2 along with a topical study on EEG signal analysis. Without compromising the extensive simulation study, a comparative study of variants of MOPSO is provided in chapter 3. Intractable problems like subset and job scheduling problems are discussed in chapters 4 and 7 by different hybrid swarm intelligence techniques. An attempt to study image enhancement by ant colony optimization is made in chapter 5. Finally, chapter 7 covers the aspect of uncertainty in data by hybrid PSO.

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.

Multiobjective Optimization

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Author : Jürgen Branke
language : en
Publisher: Springer
Release Date : 2008-10-18

Multiobjective Optimization written by Jürgen Branke and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-10-18 with Computers categories.

Multiobjective optimization deals with solving problems having not only one, but multiple, often conflicting, criteria. Such problems can arise in practically every field of science, engineering and business, and the need for efficient and reliable solution methods is increasing. The task is challenging due to the fact that, instead of a single optimal solution, multiobjective optimization results in a number of solutions with different trade-offs among criteria, also known as Pareto optimal or efficient solutions. Hence, a decision maker is needed to provide additional preference information and to identify the most satisfactory solution. Depending on the paradigm used, such information may be introduced before, during, or after the optimization process. Clearly, research and application in multiobjective optimization involve expertise in optimization as well as in decision support. This state-of-the-art survey originates from the International Seminar on Practical Approaches to Multiobjective Optimization, held in Dagstuhl Castle, Germany, in December 2006, which brought together leading experts from various contemporary multiobjective optimization fields, including evolutionary multiobjective optimization (EMO), multiple criteria decision making (MCDM) and multiple criteria decision aiding (MCDA). This book gives a unique and detailed account of the current status of research and applications in the field of multiobjective optimization. It contains 16 chapters grouped in the following 5 thematic sections: Basics on Multiobjective Optimization; Recent Interactive and Preference-Based Approaches; Visualization of Solutions; Modelling, Implementation and Applications; and Quality Assessment, Learning, and Future Challenges.

Evolutionary Algorithms For Solving Multi Objective Problems

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Author : Carlos Coello Coello
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-08-26

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 2007-08-26 with Computers categories.

Solving multi-objective problems is an evolving effort, and computer science and other related disciplines have given rise to many powerful deterministic and stochastic techniques for addressing these large-dimensional optimization problems. Evolutionary algorithms are one such generic stochastic approach that has proven to be successful and widely applicable in solving both single-objective and multi-objective problems. 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, including test suites with associated performance based on a variety of appropriate metrics, as well as serial and parallel algorithm implementations.

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.

Innovative Computing Methods And Their Applications To Engineering Problems

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Author : Nadia Nedjah
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-05-25

Innovative Computing Methods And Their Applications To Engineering Problems written by Nadia Nedjah 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 2011-05-25 with Computers categories.

The design of most modern engineering systems entails the consideration of a good trade-off between the several targets requirements to be satisfied along the system life such as high reliability, low redundancy and low operational costs. These aspects are often in conflict with one another, hence a compromise solution has to be sought. Innovative computing techniques, such as genetic algorithms, swarm intelligence, differential evolution, multi-objective evolutionary optimization, just to name few, are of great help in founding effective and reliable solution for many engineering problems. Each chapter of this book attempts to using an innovative computing technique to elegantly solve a different engineering problem.

Network Models And Optimization

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Author : Mitsuo Gen
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-07-10

Network Models And Optimization written by Mitsuo Gen 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 2008-07-10 with Technology & Engineering categories.

Network models are critical tools in business, management, science and industry. “Network Models and Optimization” presents an insightful, comprehensive, and up-to-date treatment of multiple objective genetic algorithms to network optimization problems in many disciplines, such as engineering, computer science, operations research, transportation, telecommunication, and manufacturing. The book extensively covers algorithms and applications, including shortest path problems, minimum cost flow problems, maximum flow problems, minimum spanning tree problems, traveling salesman and postman problems, location-allocation problems, project scheduling problems, multistage-based scheduling problems, logistics network problems, communication network problem, and network models in assembly line balancing problems, and airline fleet assignment problems. The book can be used both as a student textbook and as a professional reference for practitioners who use network optimization methods to model and solve problems.

Multi Objective Optimization In Computational Intelligence

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