A Brief Introduction To Continuous Evolutionary Optimization
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A Brief Introduction To Continuous Evolutionary Optimization
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Author : Oliver Kramer
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-12-04
A Brief Introduction To Continuous Evolutionary Optimization written by Oliver Kramer 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 2013-12-04 with Technology & Engineering categories.
Practical optimization problems are often hard to solve, in particular when they are black boxes and no further information about the problem is available except via function evaluations. This work introduces a collection of heuristics and algorithms for black box optimization with evolutionary algorithms in continuous solution spaces. The book gives an introduction to evolution strategies and parameter control. Heuristic extensions are presented that allow optimization in constrained, multimodal and multi-objective solution spaces. An adaptive penalty function is introduced for constrained optimization. Meta-models reduce the number of fitness and constraint function calls in expensive optimization problems. The hybridization of evolution strategies with local search allows fast optimization in solution spaces with many local optima. A selection operator based on reference lines in objective space is introduced to optimize multiple conflictive objectives. Evolutionary search is employed for learning kernel parameters of the Nadaraya-Watson estimator and a swarm-based iterative approach is presented for optimizing latent points in dimensionality reduction problems. Experiments on typical benchmark problems as well as numerous figures and diagrams illustrate the behavior of the introduced concepts and methods.
Principles In Noisy Optimization
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Author : Pratyusha Rakshit
language : en
Publisher: Springer
Release Date : 2018-11-20
Principles In Noisy Optimization written by Pratyusha Rakshit and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-20 with Computers categories.
Noisy optimization is a topic of growing interest for researchers working on mainstream optimization problems. Although several techniques for dealing with stochastic noise in optimization problems are covered in journals and conference proceedings, today there are virtually no books that approach noisy optimization from a layman’s perspective; this book remedies that gap. Beginning with the foundations of evolutionary optimization, the book subsequently explores the principles of noisy optimization in single and multi-objective settings, and presents detailed illustrations of the principles developed for application in real-world multi-agent coordination problems. Special emphasis is given to the design of intelligent algorithms for noisy optimization in real-time applications. The book is unique in terms of its content, writing style and above all its simplicity, which will appeal to readers with a broad range of backgrounds. The book is divided into 7 chapters, the first of which provides an introduction to Swarm and Evolutionary Optimization algorithms. Chapter 2 includes a thorough review of agent architectures for multi-agent coordination. In turn, Chapter 3 provides an extensive review of noisy optimization, while Chapter 4 addresses issues of noise handling in the context of single-objective optimization problems. An illustrative case study on multi-robot path-planning in the presence of measurement noise is also highlighted in this chapter. Chapter 5 deals with noisy multi-objective optimization and includes a case study on noisy multi-robot box-pushing. In Chapter 6, the authors examine the scope of various algorithms in noisy optimization problems. Lastly, Chapter 7 summarizes the main results obtained in the previous chapters and elaborates on the book’s potential with regard to real-world noisy optimization problems.
Applied Reliability For Industry 1
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Author : Abdelkhalak El Hami
language : en
Publisher: John Wiley & Sons
Release Date : 2023-05-16
Applied Reliability For Industry 1 written by Abdelkhalak El Hami 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 2023-05-16 with Technology & Engineering categories.
Applied Reliability for Industry 1 illustrates the multidisciplinary state-of-the-art science of predictive reliability. Many experts are now convinced that reliability is not limited to statistical sciences. In fact, many different disciplines interact in order to bring a product to its highest possible level of reliability, made available through today's technologies, developments and production methods. These three books, of which this is the first, propose new methods for analyzing the lifecycle of a system, enabling us to record the development phases according to development time and levels of complexity for its integration. Predictive reliability, as particularly focused on in Applied Reliability for Industry 1, examines all the engineering activities used to estimate or predict the reliability performance of the final mechatronic system.
Applications Of Evolutionary Computation
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Author : Pedro A. Castillo
language : en
Publisher: Springer Nature
Release Date : 2020-04-09
Applications Of Evolutionary Computation written by Pedro A. Castillo and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-09 with Computers categories.
This book constitutes the refereed proceedings of the 23rd European Conference on Applications of Evolutionary Computation, EvoApplications 2020, held as part of Evo*2020, in Seville, Spain, in April 2020, co-located with the Evo*2020 events EuroGP, EvoMUSART and EvoCOP. The 44 full papers presented in this book were carefully reviewed and selected from 62 submissions. The papers cover a wide spectrum of topics, ranging from applications of bio-inspired techniques on social networks, evolutionary computation in digital healthcare and personalized medicine, soft-computing applied to games, applications of deep-bioinspired algorithms, parallel and distributed systems, and evolutionary machine learning.
Artificial Neural Networks And Machine Learning Icann 2019 Deep Learning
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Author : Igor V. Tetko
language : en
Publisher: Springer Nature
Release Date : 2019-09-09
Artificial Neural Networks And Machine Learning Icann 2019 Deep Learning written by Igor V. Tetko and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-09 with Computers categories.
The proceedings set LNCS 11727, 11728, 11729, 11730, and 11731 constitute the proceedings of the 28th International Conference on Artificial Neural Networks, ICANN 2019, held in Munich, Germany, in September 2019. The total of 277 full papers and 43 short papers presented in these proceedings was carefully reviewed and selected from 494 submissions. They were organized in 5 volumes focusing on theoretical neural computation; deep learning; image processing; text and time series; and workshop and special sessions.
Evolutionary Algorithms
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Author : Alain Petrowski
language : en
Publisher: John Wiley & Sons
Release Date : 2017-04-24
Evolutionary Algorithms written by Alain Petrowski 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 2017-04-24 with Computers categories.
Evolutionary algorithms are bio-inspired algorithms based on Darwin’s theory of evolution. They are expected to provide non-optimal but good quality solutions to problems whose resolution is impracticable by exact methods. In six chapters, this book presents the essential knowledge required to efficiently implement evolutionary algorithms. Chapter 1 describes a generic evolutionary algorithm as well as the basic operators that compose it. Chapter 2 is devoted to the solving of continuous optimization problems, without constraint. Three leading approaches are described and compared on a set of test functions. Chapter 3 considers continuous optimization problems with constraints. Various approaches suitable for evolutionary methods are presented. Chapter 4 is related to combinatorial optimization. It provides a catalog of variation operators to deal with order-based problems. Chapter 5 introduces the basic notions required to understand the issue of multi-objective optimization and a variety of approaches for its application. Finally, Chapter 6 describes different approaches of genetic programming able to evolve computer programs in the context of machine learning.
Evolutionary Optimization Algorithms
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Author : Dan Simon
language : en
Publisher: John Wiley & Sons
Release Date : 2013-06-13
Evolutionary Optimization Algorithms written by Dan Simon 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 2013-06-13 with Mathematics categories.
A clear and lucid bottom-up approach to the basic principles of evolutionary algorithms Evolutionary algorithms (EAs) are a type of artificial intelligence. EAs are motivated by optimization processes that we observe in nature, such as natural selection, species migration, bird swarms, human culture, and ant colonies. This book discusses the theory, history, mathematics, and programming of evolutionary optimization algorithms. Featured algorithms include genetic algorithms, genetic programming, ant colony optimization, particle swarm optimization, differential evolution, biogeography-based optimization, and many others. Evolutionary Optimization Algorithms: Provides a straightforward, bottom-up approach that assists the reader in obtaining a clear but theoretically rigorous understanding of evolutionary algorithms, with an emphasis on implementation Gives a careful treatment of recently developed EAs including opposition-based learning, artificial fish swarms, bacterial foraging, and many others and discusses their similarities and differences from more well-established EAs Includes chapter-end problems plus a solutions manual available online for instructors Offers simple examples that provide the reader with an intuitive understanding of the theory Features source code for the examples available on the author's website Provides advanced mathematical techniques for analyzing EAs, including Markov modeling and dynamic system modeling Evolutionary Optimization Algorithms: Biologically Inspired and Population-Based Approaches to Computer Intelligence is an ideal text for advanced undergraduate students, graduate students, and professionals involved in engineering and computer science.
Adaptive Computing In Design And Manufacture Vi
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Author : I.C. Parmee
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-06-27
Adaptive Computing In Design And Manufacture Vi written by I.C. Parmee 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 2011-06-27 with Computers categories.
The Adaptive Computing in Design and Manufacture conference series has become a well-established, largely application-oriented meeting recognised by several UK Engineering Institutions and the International Society of Genetic and Evolutionary Computing. The main theme of the series relates to the integration of evolutionary and adaptive computing technologies with design and manufacturing processes whilst also taking into account complementary advanced computing technologies. Evolutionary and adaptive computing techniques continue to increase their penetration of industrial and commercial practice as awareness of their powerful search, exploration and optimisation capabilities becomes ever more prevalent, and increasing desk-top computational capability renders stochastic population-based search a far more viable proposition. There has been a significant increase in the development and integration of commercial software tools utilising adaptive computing technologies and the emergence of related commercial research and consultancy organisations supporting the introduction of best practice in terms of industrial utilisation. The book is comprised of selected papers that cover a diverse set of industrial application areas including engineering design and design environments and manufacturing process design, scheduling and control. Various aspects of search, exploration and optimisation are investigated in the context of integration with industrial processes including multi-objective and constraint satisfaction, development and utilization of meta-models, algorithm and strategy development and human-centric evolutionary approaches. The role of agent-based and neural net technologies in terms of supporting search processes and providing an alternative simulation environment is also explored. This collection of papers will be of particular interest to both industrial researchers and practitioners in addition to the academic research communities across engineering, operational research and computer science.
Simulated Evolution And Learning
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Author : Bob McKay
language : en
Publisher: Springer
Release Date : 2003-05-21
Simulated Evolution And Learning written by Bob McKay and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-05-21 with Computers categories.
This volume contains selected papers presented at the Second Asia-Paci c C- ference on Simulated Evolution and Learning (SEAL’98), from 24 to 27 Nov- ber 1998, in Canberra, Australia. SEAL’98 received a total of 92 submissions (67 papers for the regular sessions and 25 for the applications sessions). All papers were reviewed by three independent reviewers. After review, 62 papers were - cepted for oral presentation and 13 for poster presentation. Some of the accepted papers were selected for inclusion in this volume. SEAL’98 also featured a fully refereed special session on Evolutionary Computation in Power Engineering - ganised by Professor Kit Po Wong and Dr Loi Lei Lai. Two of the ve accepted papers are included in this volume. The papers included in these proceedings cover a wide range of topics in simulated evolution and learning, from self-adaptation to dynamic modelling, from reinforcement learning to agent systems, from evolutionary games to e- lutionary economics, and from novel theoretical results to successful applications, among others. SEAL’98 attracted 94 participants from 14 di erent countries, namely A- tralia, Belgium, Brazil, Germany, Iceland, India, Japan, South Korea, New Z- land, Portugal, Sweden, Taiwan, UK and the USA. It had three distinguished international scientists as keynote speakers, giving talks on natural computation (Hans-Paul Schwefel), reinforcement learning (Richard Sutton), and novel m- els in evolutionary design (John Gero). More information about SEAL’98 is still available at http://www.cs.adfa.edu.au/conference/seal98/.
Computational Intelligence Volume Ii
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Author : Hisao Ishibuchi
language : en
Publisher: EOLSS Publications
Release Date : 2015-12-30
Computational Intelligence Volume Ii written by Hisao Ishibuchi and has been published by EOLSS Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-30 with categories.
Computational intelligence is a component of Encyclopedia of Technology, Information, and Systems Management Resources in the global Encyclopedia of Life Support Systems (EOLSS), which is an integrated compendium of twenty one Encyclopedias. Computational intelligence is a rapidly growing research field including a wide variety of problem-solving techniques inspired by nature. Traditionally computational intelligence consists of three major research areas: Neural Networks, Fuzzy Systems, and Evolutionary Computation. Neural networks are mathematical models inspired by brains. Neural networks have massively parallel network structures with many neurons and weighted connections. Whereas each neuron has a simple input-output relation, a neural network with many neurons can realize a highly non-linear complicated mapping. Connection weights between neurons can be adjusted in an automated manner by a learning algorithm to realize a non-linear mapping required in a particular application task. Fuzzy systems are mathematical models proposed to handle inherent fuzziness in natural language. For example, it is very difficult to mathematically define the meaning of “cold” in everyday conversations such as “It is cold today” and “Can I have cold water”. The meaning of “cold” may be different in a different situation. Even in the same situation, a different person may have a different meaning. Fuzzy systems offer a mathematical mechanism to handle inherent fuzziness in natural language. As a result, fuzzy systems have been successfully applied to real-world problems by extracting linguistic knowledge from human experts in the form of fuzzy IF-THEN rules. Evolutionary computation includes various population-based search algorithms inspired by evolution in nature. Those algorithms usually have the following three mechanisms: fitness evaluation to measure the quality of each solution, selection to choose good solutions from the current population, and variation operators to generate offspring from parents. Evolutionary computation has high applicability to a wide range of optimization problems with different characteristics since it does not need any explicit mathematical formulations of objective functions. For example, simulation-based fitness evaluation is often used in evolutionary design. Subjective fitness evaluation by a human user is also often used in evolutionary art and music. These volumes are aimed at the following five major target audiences: University and College students Educators, Professional practitioners, Research personnel and Policy analysts, managers, and decision makers.