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Evolutionary Multi Task Optimization
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Book Synopsis Evolutionary Multi-Task Optimization by : Liang Feng
Download or read book Evolutionary Multi-Task Optimization written by Liang Feng and published by Springer Nature. This book was released on 2023-03-29 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: A remarkable facet of the human brain is its ability to manage multiple tasks with apparent simultaneity. Knowledge learned from one task can then be used to enhance problem-solving in other related tasks. In machine learning, the idea of leveraging relevant information across related tasks as inductive biases to enhance learning performance has attracted significant interest. In contrast, attempts to emulate the human brain’s ability to generalize in optimization – particularly in population-based evolutionary algorithms – have received little attention to date. Recently, a novel evolutionary search paradigm, Evolutionary Multi-Task (EMT) optimization, has been proposed in the realm of evolutionary computation. In contrast to traditional evolutionary searches, which solve a single task in a single run, evolutionary multi-tasking algorithm conducts searches concurrently on multiple search spaces corresponding to different tasks or optimization problems, each possessing a unique function landscape. By exploiting the latent synergies among distinct problems, the superior search performance of EMT optimization in terms of solution quality and convergence speed has been demonstrated in a variety of continuous, discrete, and hybrid (mixture of continuous and discrete) tasks. This book discusses the foundations and methodologies of developing evolutionary multi-tasking algorithms for complex optimization, including in domains characterized by factors such as multiple objectives of interest, high-dimensional search spaces and NP-hardness.
Book Synopsis Recent Advances in Evolutionary Multi-objective Optimization by : Slim Bechikh
Download or read book Recent Advances in Evolutionary Multi-objective Optimization written by Slim Bechikh and published by Springer. This book was released on 2016-08-09 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Evolutionary Multi-Criterion Optimization by : Hisao Ishibuchi
Download or read book Evolutionary Multi-Criterion Optimization written by Hisao Ishibuchi and published by Springer Nature. This book was released on 2021-03-24 with total page 781 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 11th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2021 held in Shenzhen, China, in March 2021. The 47 full papers and 14 short papers were carefully reviewed and selected from 120 submissions. The papers are divided into the following topical sections: theory; algorithms; dynamic multi-objective optimization; constrained multi-objective optimization; multi-modal optimization; many-objective optimization; performance evaluations and empirical studies; EMO and machine learning; surrogate modeling and expensive optimization; MCDM and interactive EMO; and applications.
Book Synopsis Multi-Objective Optimization using Evolutionary Algorithms by : Kalyanmoy Deb
Download or read book Multi-Objective Optimization using Evolutionary Algorithms written by Kalyanmoy Deb and published by John Wiley & Sons. This book was released on 2001-07-05 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimierung mit mehreren Zielen, evolutionäre Algorithmen: Dieses Buch wendet sich vorrangig an Einsteiger, denn es werden kaum Vorkenntnisse vorausgesetzt. Geboten werden alle notwendigen Grundlagen, um die Theorie auf Probleme der Ingenieurtechnik, der Vorhersage und der Planung anzuwenden. Der Autor gibt auch einen Ausblick auf Forschungsaufgaben der Zukunft.
Book Synopsis Evolutionary Computation & Swarm Intelligence by : Fabio Caraffini
Download or read book Evolutionary Computation & Swarm Intelligence written by Fabio Caraffini and published by MDPI. This book was released on 2020-11-25 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: The vast majority of real-world problems can be expressed as an optimisation task by formulating an objective function, also known as cost or fitness function. The most logical methods to optimise such a function when (1) an analytical expression is not available, (2) mathematical hypotheses do not hold, and (3) the dimensionality of the problem or stringent real-time requirements make it infeasible to find an exact solution mathematically are from the field of Evolutionary Computation (EC) and Swarm Intelligence (SI). The latter are broad and still growing subjects in Computer Science in the study of metaheuristic approaches, i.e., those approaches which do not make any assumptions about the problem function, inspired from natural phenomena such as, in the first place, the evolution process and the collaborative behaviours of groups of animals and communities, respectively. This book contains recent advances in the EC and SI fields, covering most themes currently receiving a great deal of attention such as benchmarking and tunning of optimisation algorithms, their algorithm design process, and their application to solve challenging real-world problems to face large-scale domains.
Book Synopsis Evolutionary Multi-objective Optimization in Uncertain Environments by : Chi-Keong Goh
Download or read book Evolutionary Multi-objective Optimization in Uncertain Environments written by Chi-Keong Goh and published by Springer Science & Business Media. This book was released on 2009-03-09 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Evolutionary Multi-Criterion Optimization by : Michael Emmerich
Download or read book Evolutionary Multi-Criterion Optimization written by Michael Emmerich and published by Springer Nature. This book was released on 2023-03-09 with total page 646 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 12th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2022 held in Leiden, The Netherlands, during March 20-24, 2023. The 44 regular papers presented in this book were carefully reviewed and selected from 65 submissions. The papers are divided into the following topical sections: Algorithm Design and Engineering; Machine Learning and Multi-criterion Optimization; Benchmarking and Performance Assessment; Indicator Design and Complexity Analysis; Applications in Real World Domains; and Multi-Criteria Decision Making and Interactive Algorithms..
Book Synopsis Cognitive Multitasking – Towards Augmented Intelligence by : Yew Soon Ong
Download or read book Cognitive Multitasking – Towards Augmented Intelligence written by Yew Soon Ong and published by Frontiers Media SA. This book was released on 2021-03-04 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Procedural Content Generation in Games by : Noor Shaker
Download or read book Procedural Content Generation in Games written by Noor Shaker and published by Springer. This book was released on 2016-10-18 with total page 247 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the most up-to-date coverage of procedural content generation (PCG) for games, specifically the procedural generation of levels, landscapes, items, rules, quests, or other types of content. Each chapter explains an algorithm type or domain, including fractal methods, grammar-based methods, search-based and evolutionary methods, constraint-based methods, and narrative, terrain, and dungeon generation. The authors are active academic researchers and game developers, and the book is appropriate for undergraduate and graduate students of courses on games and creativity; game developers who want to learn new methods for content generation; and researchers in related areas of artificial intelligence and computational intelligence.
Book Synopsis Evolutionary Multiobjective Optimization by : Ajith Abraham
Download or read book Evolutionary Multiobjective Optimization written by Ajith Abraham and published by Springer Science & Business Media. This book was released on 2005-09-05 with total page 313 pages. Available in PDF, EPUB and Kindle. Book excerpt: Evolutionary Multi-Objective Optimization is an expanding field of research. This book brings a collection of papers with some of the most recent advances in this field. The topic and content is currently very fashionable and has immense potential for practical applications and includes contributions from leading researchers in the field. Assembled in a compelling and well-organised fashion, Evolutionary Computation Based Multi-Criteria Optimization will prove beneficial for both academic and industrial scientists and engineers engaged in research and development and application of evolutionary algorithm based MCO. Packed with must-find information, this book is the first to comprehensively and clearly address the issue of evolutionary computation based MCO, and is an essential read for any researcher or practitioner of the technique.
Book Synopsis Bio-Inspired Computing: Theories and Applications by : Linqiang Pan
Download or read book Bio-Inspired Computing: Theories and Applications written by Linqiang Pan and published by Springer Nature. This book was released on with total page 415 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Applications of Multi-objective Evolutionary Algorithms by : Carlos A. Coello Coello
Download or read book Applications of Multi-objective Evolutionary Algorithms written by Carlos A. Coello Coello and published by World Scientific. This book was released on 2004 with total page 792 pages. Available in PDF, EPUB and Kindle. Book excerpt: - Detailed MOEA applications discussed by international experts - State-of-the-art practical insights in tackling statistical optimization with MOEAs - A unique monograph covering a wide spectrum of real-world applications - Step-by-step discussion of MOEA applications in a variety of domains
Book Synopsis Multiobjective Optimization by : Jürgen Branke
Download or read book Multiobjective Optimization written by Jürgen Branke and published by Springer. This book was released on 2008-10-18 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Simulated Evolution and Learning by : Yuhui Shi
Download or read book Simulated Evolution and Learning written by Yuhui Shi and published by Springer. This book was released on 2017-11-01 with total page 1041 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 11th International Conference on Simulated Evolution and Learning, SEAL 2017, held in Shenzhen, China, in November 2017. The 85 papers presented in this volume were carefully reviewed and selected from 145 submissions. They were organized in topical sections named: evolutionary optimisation; evolutionary multiobjective optimisation; evolutionary machine learning; theoretical developments; feature selection and dimensionality reduction; dynamic and uncertain environments; real-world applications; adaptive systems; and swarm intelligence.
Book Synopsis Data-Driven Evolutionary Optimization by : Yaochu Jin
Download or read book Data-Driven Evolutionary Optimization written by Yaochu Jin and published by Springer Nature. This book was released on 2021-06-28 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intended for researchers and practitioners alike, this book covers carefully selected yet broad topics in optimization, machine learning, and metaheuristics. Written by world-leading academic researchers who are extremely experienced in industrial applications, this self-contained book is the first of its kind that provides comprehensive background knowledge, particularly practical guidelines, and state-of-the-art techniques. New algorithms are carefully explained, further elaborated with pseudocode or flowcharts, and full working source code is made freely available. This is followed by a presentation of a variety of data-driven single- and multi-objective optimization algorithms that seamlessly integrate modern machine learning such as deep learning and transfer learning with evolutionary and swarm optimization algorithms. Applications of data-driven optimization ranging from aerodynamic design, optimization of industrial processes, to deep neural architecture search are included.
Book Synopsis Advances in Swarm Intelligence by : Ying Tan
Download or read book Advances in Swarm Intelligence written by Ying Tan and published by Springer Nature. This book was released on 2023-07-07 with total page 502 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set LNCS 13968 and 13969 constitutes the proceedings of the 14th International Conference on Advances in Swarm Intelligence, ICSI 2023, which took place in Shenzhen, China, China, in July 2023. The theme of this year’s conference was “Serving Life with Swarm Intelligence”. The 81 full papers presented were carefully reviewed and selected from 170 submissions. The papers are organized into 12 cohesive sections covering major topics of swarm intelligence research and its development and applications. The papers of the first part cover topics such as: Swarm Intelligence Computing; Swarm Intelligence Optimization Algorithms; Particle Swarm Optimization Algorithms; Genetic Algorithms; Optimization Computing Algorithms; Neural Network Search & Large-Scale Optimization; Multi-objective Optimization.
Author :Ricardo H.C. Takahashi Publisher :Springer Science & Business Media ISBN 13 :3642198929 Total Pages :634 pages Book Rating :4.6/5 (421 download)
Book Synopsis Evolutionary Multi-Criterion Optimization by : Ricardo H.C. Takahashi
Download or read book Evolutionary Multi-Criterion Optimization written by Ricardo H.C. Takahashi and published by Springer Science & Business Media. This book was released on 2011-03-14 with total page 634 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 6th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2011, held in Ouro Preto, Brazil, in April 2011. The 42 revised full papers presented were carefully reviewed and selected from 83 submissions. The papers deal with fundamental questions of EMO theory, such as the development of algorithmically efficient tools for the evaluation of solution-set quality , the theoretical questions related to solution archiving and others. They report on the continuing effort in the development of algorithms, either for dealing with particular classes of problems or for new forms of processing the problem information. Almost one third of the papers is related to EMO applications in a diversity of fields. Eleven papers are devoted to promote the interaction with the related field of Multi-Criterion Decision Making (MCDM).
