Multi Objective Memetic Algorithms

Author : Ferrante Neri
Publisher : Springer Science & Business Media
ISBN 13 : 3642232469
Total Pages : 376 pages
Book Rating : 4.66/5 ( download)

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Download or read book Handbook of Memetic Algorithms written by Ferrante Neri and published by Springer Science & Business Media. This book was released on 2011-10-18 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Memetic Algorithms (MAs) are computational intelligence structures combining multiple and various operators in order to address optimization problems. The combination and interaction amongst operators evolves and promotes the diffusion of the most successful units and generates an algorithmic behavior which can handle complex objective functions and hard fitness landscapes. “Handbook of Memetic Algorithms” organizes, in a structured way, all the the most important results in the field of MAs since their earliest definition until now. A broad review including various algorithmic solutions as well as successful applications is included in this book. Each class of optimization problems, such as constrained optimization, multi-objective optimization, continuous vs combinatorial problems, uncertainties, are analysed separately and, for each problem, memetic recipes for tackling the difficulties are given with some successful examples. Although this book contains chapters written by multiple authors, a great attention has been given by the editors to make it a compact and smooth work which covers all the main areas of computational intelligence optimization. It is not only a necessary read for researchers working in the research area, but also a useful handbook for practitioners and engineers who need to address real-world optimization problems. In addition, the book structure makes it an interesting work also for graduate students and researchers is related fields of mathematics and computer science.

Author : Ferrante Neri
Publisher : Springer
ISBN 13 : 9783642269424
Total Pages : 0 pages
Book Rating : 4.27/5 ( download)

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Download or read book Handbook of Memetic Algorithms written by Ferrante Neri and published by Springer. This book was released on 2013-11-30 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Memetic Algorithms (MAs) are computational intelligence structures combining multiple and various operators in order to address optimization problems. The combination and interaction amongst operators evolves and promotes the diffusion of the most successful units and generates an algorithmic behavior which can handle complex objective functions and hard fitness landscapes. “Handbook of Memetic Algorithms” organizes, in a structured way, all the the most important results in the field of MAs since their earliest definition until now. A broad review including various algorithmic solutions as well as successful applications is included in this book. Each class of optimization problems, such as constrained optimization, multi-objective optimization, continuous vs combinatorial problems, uncertainties, are analysed separately and, for each problem, memetic recipes for tackling the difficulties are given with some successful examples. Although this book contains chapters written by multiple authors, a great attention has been given by the editors to make it a compact and smooth work which covers all the main areas of computational intelligence optimization. It is not only a necessary read for researchers working in the research area, but also a useful handbook for practitioners and engineers who need to address real-world optimization problems. In addition, the book structure makes it an interesting work also for graduate students and researchers is related fields of mathematics and computer science.

Author : Chi-Keong Goh
Publisher : Springer Science & Business Media
ISBN 13 : 354088050X
Total Pages : 399 pages
Book Rating : 4.09/5 ( download)

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Download or read book Multi-Objective Memetic Algorithms written by Chi-Keong Goh and published by Springer Science & Business Media. This book was released on 2009-02-26 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt: The application of sophisticated evolutionary computing approaches for solving complex problems with multiple conflicting objectives in science and engineering have increased steadily in the recent years. Within this growing trend, Memetic algorithms are, perhaps, one of the most successful stories, having demonstrated better efficacy in dealing with multi-objective problems as compared to its conventional counterparts. Nonetheless, researchers are only beginning to realize the vast potential of multi-objective Memetic algorithm and there remain many open topics in its design. This book presents a very first comprehensive collection of works, written by leading researchers in the field, and reflects the current state-of-the-art in the theory and practice of multi-objective Memetic algorithms. "Multi-Objective Memetic algorithms" is organized 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 Memetic algorithms and multi-objective optimization.

Author : William E. Hart
Publisher : Springer
ISBN 13 : 3540323635
Total Pages : 406 pages
Book Rating : 4.31/5 ( download)

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Download or read book Recent Advances in Memetic Algorithms written by William E. Hart and published by Springer. This book was released on 2006-06-22 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: Memetic algorithms are evolutionary algorithms that apply a local search process to refine solutions to hard problems. Memetic algorithms are the subject of intense scientific research and have been successfully applied to a multitude of real-world problems ranging from the construction of optimal university exam timetables, to the prediction of protein structures and the optimal design of space-craft trajectories. This monograph presents a rich state-of-the-art gallery of works on memetic algorithms. Recent Advances in Memetic Algorithms is the first book that focuses on this technology as the central topical matter. This book gives a coherent, integrated view on both good practice examples and new trends including a concise and self-contained introduction to memetic algorithms. It is a necessary read for postgraduate students and researchers interested in recent advances in search and optimization technologies based on memetic algorithms, but can also be used as complement to undergraduate textbooks on artificial intelligence.

Author : Holger H. Hoos
Publisher : Morgan Kaufmann
ISBN 13 : 1558608729
Total Pages : 678 pages
Book Rating : 4.26/5 ( download)

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Download or read book Stochastic Local Search written by Holger H. Hoos and published by Morgan Kaufmann. This book was released on 2005 with total page 678 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic local search (SLS) algorithms are among the most prominent and successful techniques for solving computationally difficult problems. Offering a systematic treatment of SLS algorithms, this book examines the general concepts and specific instances of SLS algorithms and considers their development, analysis and application.

Author : Abhishek Gupta
Publisher : Springer
ISBN 13 : 3030027295
Total Pages : 104 pages
Book Rating : 4.92/5 ( download)

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Download or read book Memetic Computation written by Abhishek Gupta and published by Springer. This book was released on 2018-12-18 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book bridges the widening gap between two crucial constituents of computational intelligence: the rapidly advancing technologies of machine learning in the digital information age, and the relatively slow-moving field of general-purpose search and optimization algorithms. With this in mind, the book serves to offer a data-driven view of optimization, through the framework of memetic computation (MC). The authors provide a summary of the complete timeline of research activities in MC – beginning with the initiation of memes as local search heuristics hybridized with evolutionary algorithms, to their modern interpretation as computationally encoded building blocks of problem-solving knowledge that can be learned from one task and adaptively transmitted to another. In the light of recent research advances, the authors emphasize the further development of MC as a simultaneous problem learning and optimization paradigm with the potential to showcase human-like problem-solving prowess; that is, by equipping optimization engines to acquire increasing levels of intelligence over time through embedded memes learned independently or via interactions. In other words, the adaptive utilization of available knowledge memes makes it possible for optimization engines to tailor custom search behaviors on the fly – thereby paving the way to general-purpose problem-solving ability (or artificial general intelligence). In this regard, the book explores some of the latest concepts from the optimization literature, including, the sequential transfer of knowledge across problems, multitasking, and large-scale (high dimensional) search, systematically discussing associated algorithmic developments that align with the general theme of memetics. The presented ideas are intended to be accessible to a wide audience of scientific researchers, engineers, students, and optimization practitioners who are familiar with the commonly used terminologies of evolutionary computation. A full appreciation of the mathematical formalizations and algorithmic contributions requires an elementary background in probability, statistics, and the concepts of machine learning. A prior knowledge of surrogate-assisted/Bayesian optimization techniques is useful, but not essential.

Author : Farouk Yalaoui
Publisher : Springer Nature
ISBN 13 : 3030589307
Total Pages : 444 pages
Book Rating : 4.01/5 ( download)

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Download or read book Heuristics for Optimization and Learning written by Farouk Yalaoui and published by Springer Nature. This book was released on 2020-12-15 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a new contribution aiming to give some last research findings in the field of optimization and computing. This work is in the same field target than our two previous books published: “Recent Developments in Metaheuristics” and “Metaheuristics for Production Systems”, books in Springer Series in Operations Research/Computer Science Interfaces. The challenge with this work is to gather the main contribution in three fields, optimization technique for production decision, general development for optimization and computing method and wider spread applications. The number of researches dealing with decision maker tool and optimization method grows very quickly these last years and in a large number of fields. We may be able to read nice and worthy works from research developed in chemical, mechanical, computing, automotive and many other fields.

Author : Carlos Coello Coello
Publisher : Springer Science & Business Media
ISBN 13 : 0387367977
Total Pages : 810 pages
Book Rating : 4.72/5 ( download)

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Download or read book Evolutionary Algorithms for Solving Multi-Objective Problems written by Carlos Coello Coello and published by Springer Science & Business Media. This book was released on 2007-08-26 with total page 810 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Author : Carlos Coello Coello
Publisher : Springer Science & Business Media
ISBN 13 : 0387332545
Total Pages : 810 pages
Book Rating : 4.43/5 ( download)

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Download or read book Evolutionary Algorithms for Solving Multi-Objective Problems written by Carlos Coello Coello and published by Springer Science & Business Media. This book was released on 2007-09-18 with total page 810 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Author : Günter Rudolph
Publisher : Springer
ISBN 13 : 3540877002
Total Pages : 1183 pages
Book Rating : 4.04/5 ( download)

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Download or read book Parallel Problem Solving from Nature - PPSN X written by Günter Rudolph and published by Springer. This book was released on 2008-09-16 with total page 1183 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 10th International Conference on Parallel Problem Solving from Nature, PPSN 2008, held in Dortmund, Germany, in September 2008. The 114 revised full papers presented were carefully reviewed and selected from 206 submissions. The conference covers a wide range of topics, such as evolutionary computation, quantum computation, molecular computation, neural computation, artificial life, swarm intelligence, artificial ant systems, artificial immune systems, self-organizing systems, emergent behaviors, and applications to real-world problems. The paper are organized in topical sections on formal theory, new techniques, experimental analysis, multiobjective optimization, hybrid methods, and applications.