Multi-objective Swarm Intelligence

Multi-objective Swarm Intelligence

Author: Satchidananda Dehuri

Publisher: Springer

Published: 2015-03-10

Total Pages: 209

ISBN-13: 3662463091

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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.


Swarm Intelligence for Multi-objective Problems in Data Mining

Swarm Intelligence for Multi-objective Problems in Data Mining

Author: Carlos Coello Coello

Publisher: Springer Science & Business Media

Published: 2009-09-28

Total Pages: 296

ISBN-13: 3642036244

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The purpose of this book is to collect contributions that are at the intersection of multi-objective optimization, swarm intelligence (specifically, particle swarm optimization and ant colony optimization) and data mining.


Multi-Objective Swarm Intelligent Systems

Multi-Objective Swarm Intelligent Systems

Author: Leandro dos Santos Coelho

Publisher: Springer Science & Business Media

Published: 2009-11-19

Total Pages: 228

ISBN-13: 3642051642

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This book covers the latest in multi-objective swarm intelligence and cooperative behavior. It contains innovative and intriguing applications as well as additions to the methodology and theory of genetic programming.


Multi-Objective Optimization using Artificial Intelligence Techniques

Multi-Objective Optimization using Artificial Intelligence Techniques

Author: Seyedali Mirjalili

Publisher: Springer

Published: 2019-07-24

Total Pages: 58

ISBN-13: 3030248356

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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.


Handbook of Swarm Intelligence

Handbook of Swarm Intelligence

Author: Bijaya Ketan Panigrahi

Publisher: Springer Science & Business Media

Published: 2011-02-04

Total Pages: 538

ISBN-13: 364217390X

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From nature, we observe swarming behavior in the form of ant colonies, bird flocking, animal herding, honey bees, swarming of bacteria, and many more. It is only in recent years that researchers have taken notice of such natural swarming systems as culmination of some form of innate collective intelligence, albeit swarm intelligence (SI) - a metaphor that inspires a myriad of computational problem-solving techniques. In computational intelligence, swarm-like algorithms have been successfully applied to solve many real-world problems in engineering and sciences. This handbook volume serves as a useful foundational as well as consolidatory state-of-art collection of articles in the field from various researchers around the globe. It has a rich collection of contributions pertaining to the theoretical and empirical study of single and multi-objective variants of swarm intelligence based algorithms like particle swarm optimization (PSO), ant colony optimization (ACO), bacterial foraging optimization algorithm (BFOA), honey bee social foraging algorithms, and harmony search (HS). With chapters describing various applications of SI techniques in real-world engineering problems, this handbook can be a valuable resource for researchers and practitioners, giving an in-depth flavor of what SI is capable of achieving.


Evolutionary Multi-Criterion Optimization

Evolutionary Multi-Criterion Optimization

Author: Matthias Ehrgott

Publisher: Springer Science & Business Media

Published: 2009-03-26

Total Pages: 599

ISBN-13: 3642010199

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This book constitutes the refereed proceedings of the 5th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2009, held in Nantes, France in April 2009. The 39 revised full papers presented together with 5 invited talks were carefully reviewed and selected from 72 submissions. The papers are organized in topical sections on theoretical analysis, uncertainty and noise, algorithm development, performance analysis and comparison, applications, MCDM Track, Many objectives, alternative methods, as well as EMO and MCDA.


Multi-Objective Optimization in Computational Intelligence: Theory and Practice

Multi-Objective Optimization in Computational Intelligence: Theory and Practice

Author: Thu Bui, Lam

Publisher: IGI Global

Published: 2008-05-31

Total Pages: 496

ISBN-13: 1599045001

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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.


Theory and New Applications of Swarm Intelligence

Theory and New Applications of Swarm Intelligence

Author: Rafael Parpinelli

Publisher: BoD – Books on Demand

Published: 2012-03-16

Total Pages: 207

ISBN-13: 9535103644

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The field of research that studies the emergent collective intelligence of self-organized and decentralized simple agents is referred to as Swarm Intelligence. It is based on social behavior that can be observed in nature, such as flocks of birds, fish schools and bee hives, where a number of individuals with limited capabilities are able to come to intelligent solutions for complex problems. The computer science community have already learned about the importance of emergent behaviors for complex problem solving. Hence, this book presents some recent advances on Swarm Intelligence, specially on new swarm-based optimization methods and hybrid algorithms for several applications. The content of this book allows the reader to know more both theoretical and technical aspects and applications of Swarm Intelligence.


Evolutionary and Swarm Intelligence Algorithms

Evolutionary and Swarm Intelligence Algorithms

Author: Jagdish Chand Bansal

Publisher: Springer

Published: 2018-06-06

Total Pages: 194

ISBN-13: 3319913417

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This book is a delight for academics, researchers and professionals working in evolutionary and swarm computing, computational intelligence, machine learning and engineering design, as well as search and optimization in general. It provides an introduction to the design and development of a number of popular and recent swarm and evolutionary algorithms with a focus on their applications in engineering problems in diverse domains. The topics discussed include particle swarm optimization, the artificial bee colony algorithm, Spider Monkey optimization algorithm, genetic algorithms, constrained multi-objective evolutionary algorithms, genetic programming, and evolutionary fuzzy systems. A friendly and informative treatment of the topics makes this book an ideal reference for beginners and those with experience alike.


Advanced Methodologies and Technologies in Artificial Intelligence, Computer Simulation, and Human-computer Interaction

Advanced Methodologies and Technologies in Artificial Intelligence, Computer Simulation, and Human-computer Interaction

Author: Mehdi Khosrow-Pour

Publisher: Engineering Science Reference

Published: 2018-09-30

Total Pages: 0

ISBN-13: 9781522573685

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As modern technologies continue to develop and evolve, the ability of users to adapt with new systems becomes a paramount concern. Research into new ways for humans to make use of advanced computers and other such technologies through artificial intelligence and computer simulation is necessary to fully realize the potential of tools in the 21st century. Advanced Methodologies and Technologies in Artificial Intelligence, Computer Simulation, and Human-Computer Interaction provides emerging research in advanced trends in robotics, AI, simulation, and human-computer interaction. Readers will learn about the positive applications of artificial intelligence and human-computer interaction in various disciples such as business and medicine. This book is a valuable resource for IT professionals, researchers, computer scientists, and researchers invested in assistive technologies, artificial intelligence, robotics, and computer simulation.