CRC Press, 2009, -377 p. Essentially, this book is about algorithmic developments in the context of genetic algorithms (GAs) and genetic programming (GP); we also describe their applications to significant combinatorial optimization problems as well as structure identification using HeuristicLab as a platform for algorithm development. The main issue of the theoretical...
Springer, 2016. — 143 p. This book presents powerful techniques for solving global optimization problems on manifolds by means of evolutionary algorithms, and shows in practice how these techniques can be applied to solve real-world problems. It describes recent findings and well-known key facts in general and differential topology, revisiting them all in the context of...
Springer, 2008, -247 p. This book is the result of an effort to create very efficient search algorithms with a bound cost in their performance and their implementation. Solving optimization and learning problems in academy and industry is of major importance nowadays, not only in computer science, but also in operations research, mathematics, and in almost any domain in daily...
Berlin: Springer, 2008. — 369 p. Darwinian evolutionary theory is one of the most important theories in human history for it has equipped us with a valuable tool to understand the amazing world around us. There can be little surprise, therefore, that Evolutionary Computation (EC), inspired by natural evolution, has been so successful in providing high-quality solutions in a...
New York: Springer, 2006. - 578 p. This book is an adaptation of notes that have been used to teach a class in evolutionary computation at Iowa State University for eight years. A number of people have used the notes over the years, and by publishing them in book form I hope to make the material available to a wider audience. It is important to state clearly what this book is...
Springer, 1999. — 369 p. This book describes methods for developing multiobjective solutions to common production scheduling situations modeled in the literature as flowshops, job shops and open shops. The methodology is metaheuristic, one inspired by how nature has evolved a multitude of coexisting species of living beings on earth. Multiobjective scheduling situations are...
Springer, 2020. — 171 p. — ISBN13: 9783030523558. This textbook introduces readers to the recent advances in the emerging field of genetic design automation (GDA). Starting with an introduction and the basic concepts of molecular biology, the authors provide an overview of various genetic design automation tools. The authors then present the DVASim tool (Dynamic Virtual...
Springer, 2007. — 320 p. Genetic algorithms (GAs) are randomized search and optimization techniques guided by the principles of evolution and natural genetics; they have a large amount of implicit parallelism. GAs perform multimodal search in complex landscapes and provide near-optimal solutions for objective or fitness function of an optimization problem. They have...
Springer, 2018. — 194 p. — ISBN: 3319913395. 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...
San Francisco: Morgan Kaufmann, 1998. — 481 p. Since the early 1990s, genetic programming (GP) — a discipline whose goal is to enable the automatic generation of computer programs — has emerged as one of the most promising paradigms for fast, productive software development. GP combines biological metaphors gleaned from Darwin's theory of evolution with computer-science...
Springer, 1998. — 471 p. First European Workshop, EuroGP'98, Paris, France, April 14-15, 1998, Proceedings. This book constitutes the refereed proceedings of the First European Workshop on Genetic Programming, EuroGP'98, held in Paris, France, in April 1998, under the sponsorship of EvoNet, the European Network of Excellence in Evolutionary Computing. The volume presents 12...
Springer, 2022. — 220 p. — (Genetic and Evolutionary Computation). — ISBN13: 9789811681127. This book, written by the foremost international researchers and practitioners of genetic programming (GP), explores the synergy between theoretical and empirical results on real-world problems, producing a comprehensive view of the state of the art in GP. In this year’s edition, the...
Springer, 2015. — 184 p. This book is structured in 7 chapters, as follows. Chapter 1 Introduction. Chapter 2 [Decision-Tree Induction]. This chapter presents the origins, basic concepts, detailed components of top-downinduction, and also other decision-tree induction strategies. Chapter 3 [Evolutionary Algorithms and Hyper-Heuristics]. This chapter covers the origins, basic...
Springer, 2006. — 221 p. Rigorously proven upper and lower run-time bounds for simplified evolutionary algorithms on artificial optimization problems on the one hand and endless tables of benchmark results for real-world algorithms on today’s or yesterday’s hardware on the other, is that all one can do to justify their invention, existence, or even spreading use? Thomas...
Springer, 2001. — 393. Evolutionary Algorithms (EA), such as Evolution Strategies (ES), Genetic Algorithms (GA), and Evolutionary Programming (EP), have found a broad acceptance as robust optimization algorithms in the last ten years. The idea of optimizing systems through imitating nature and applying the "genetic operators" such as selection, mutation, and recombination has a...
Springer, 2015. — 181 p. This book describes how evolutionary algorithms (EA), including genetic algorithms (GA) and particle swarm optimization (PSO) can be utilized for solving multi-objective optimization problems in the area of embedded and VLSI system design. Many complex engineering optimization problems can be modelled as multi-objective formulations. This book provides...
New York: Springer, 2019. — 464 p. What Does This Book Cover? The Diversity of Life Foraging Interactions Choice of Foraging Strategy Payoffs of Foraging Strategies Alternative Approaches to Foraging Structure of Book Perspectives on Foraging Optimal Foraging Theory Currency Constraints Optimal Diet Model Critiques of OFT Foraging as a Game Hawk–Dove Game Predator–Prey Models...
Springer Cham, 2023. — 360 p. — (Natural Computing Series) — eBook ISBN: 978-3-031-25263-1. This book presents the state-of-the-art, current challenges, and future perspectives for the field of many-criteria optimization and decision analysis. The field recognizes that real-life problems often involve trying to balance a multiplicity of considerations simultaneously – such as...
Springer, 2011. — 136 p. — ISBN: 978-1447121787 The book describes the world's first successful experiment in fully automated board game design. Evolutionary methods were used to derive new rule sets within a custom game description language, and self-play trials used to estimate each derived game's potential to interest human players. The end result is a number of new and...
AlgorithmAfternoon.com, 2024. — 226 p. — ASIN: B0D2G697MT. Are you a software developer looking to harness the power of genetic algorithms to solve complex optimization problems? "Genetic Algorithm Afternoon: A Practical Guide for Software Developers" is your go-to resource for mastering this innovative and powerful technique. Whether you're a beginner or an experienced...
Pragmatic Bookshelf, 2019. — 234 p. — (Pragmatic Programmers). — ISBN: 168050620X. Self-driving cars, natural language recognition, and online recommendation engines are all possible thanks to Machine Learning. Now you can create your own genetic algorithms, nature-inspired swarms, Monte Carlo simulations, cellular automata, and clusters. Learn how to test your ML code and dive...
Springer, 2014. — 286 p. Evolution and complexity characterize both biological and artificial life – by direct modeling of biological processes and the creation of populations of interacting entities from which complex behaviors can emerge and evolve. This edited book includes invited chapters from leading scientists in the fields of artificial life, complex systems, and...
Springer, 2001, -171 p. Researchers and practitioners alike are increasingly turning to search, optimization, and machine-learning procedures based on natural selection and natural genetics to solve problems across the spectrum of human endeavor. These genetic algorithms and techniques of evolutionary computation are solving problems and inventing new hardware and software that...
World Scientific Publishing Co. Pte. Ltd., 2004. — 761 p. This book presents an extensive variety of multi-objective problems across diverse disciplines, along with statistical solutions using multi-objective evolutionary algorithms (MOEAs). The topics discussed serve to promote a wider understanding as well as the use of MOEAs, the aim being to find good solutions for...
New York. USA: Nova Science Publishers, Inc., 2017. — 127 p. — (Computer Science, Technology and Applications). — ISBN: 1536118567. In Chapter One, a revision and complementary analysis of three interesting cases where stochastic strategies are applied to get the optimal design of intensified schemes is presented. The revisited cases include multicomponent, extractive and...
Springer, 2008. — 340 p. Differential evolution is arguably one of the hottest topics in today's computational intelligence research. This book seeks to present a comprehensive study of the state of the art in this technology and also directions for future research. The fourteen chapters of this book have been written by leading experts in the area. The first seven chapters...
Book, 64 p, March 2002 Optimization and hill climbing The simplex method Iterated simplex A set of test problems Performance of the simplex and iterated simplex methods Evolution optimization and genetic algorithms Biological evolution The power of cumulative selection A basic genetic algorithm Information transfer in genetic algorithms A genetic algorithm for numerical...
ITexLi, 2024. — 79 p. — ISBN: 1837692955 9781837692958 1837692947 9781837692941 1837692963 9781837692965. This volume presents a series of scientific contributions that delve into the intricate theoretical foundations and practical nuances of genetic algorithms (GAs). This book serves as a testament to the scientific advancements within the field, inviting readers to explore...
Kluwer, 2002. — 491. The applications of genetic algorithms and genetic programming to computation finance have been seen over the last decade in various journal publications, chapters in books, and magazine articles. Their relevance to computational finance is further strengthened when these tools are already deployed and used in many financial firms. Given the trend, these...
Springer, 2010. — 255 p. One major branch of enhancing the performance of evolutionary algorithms is the exploitation of linkage learning. This monograph aims to capture the recent progress of linkage learning, by compiling a series of focused technical chapters to keep abreast of the developments and trends in the area of linkage. In evolutionary algorithms, linkage models the...
Springer, 2006. — 135 p. There are two primary objectives of this monograph. The first goal is to identify certain limits of genetic algorithms that use only fitness for learning genetic linkage. Both an explanatory theory and experimental results to support the theory are provided. The other goal is to propose a better design of the linkage learning genetic algorithm. After...
Springer, 2008. — 483 p. In recent years, the issue of linkage in GEAs has garnered greater attention and recognition from researchers. Conventional approaches that rely much on ad hoc tweaking of parameters to control the search by balancing the level of exploitation and exploration are grossly inadequate. As shown in the work reported here, such parameters tweaking based...
Springer, 2012. — 469 p. When applications or systems utilising EAs reach the production stage, off-the-shelf versions of these methods are typically replaced by dedicated algorithm variants. These specialised EAs often use tailored reproduction operators, search spaces differing significantly from the well-known binary or tree-based encodings, non-trivial genotype-phenotype...
Second Edition. — Springer, 2007, -809 p. The response of the multiobjective optimization community to our first edition in 2002 was extremely enthusiastic. Many have indicated their use of our monograph to gain insight to the interdisciplinary nature of multiobjective optimization employing evolutionary algorithms. Others are appreciative for our providing them a foundation...
Springer, 2005. — 926 p. Third International Conference, EMO 2005, Guanajuato, Mexico, March 9-11, 2005, Proceedings. This book constitutes the refereed proceedings of the Third International Conference on Evolutionary Multi-Criterion Optimization, EMO 2005, held in Guanajuato, Mexico, in March 2005. The 59 revised full papers presented together with 2 invited papers and the...
Springer, 2006. — 371 p. 9th European Conference, EuroGP 2006, Budapest, Hungary, April 10-12, 2006. Proceedings. This book constitutes the refereed proceedings of the 9th European Conference on Genetic Programming, EuroGP 2006, held in Budapest, Hungary, in April 2006, colocated with EvoCOP 2006. The 21 revised plenary papers and 11 revised poster papers were carefully...
World Scientific, 2001. — 489 p. The book summarizes and analyzes the novel field of genetic fuzzy systems, paying special attention to genetic algorithms that adapt and learn the knowledge base of a fuzzy-rule-based system. It introduces the general concepts, foundations and design principles of genetic fuzzy systems and covers the topic of genetic tuning of fuzzy systems. It...
Springer, 2008. — 333 p. Combinatorial optimisation is a ubiquitous discipline whose usefulness spans vast applications domains. The intrinsic complexity of most combinatorial optimisation problems makes classical methods unaffordable in many cases. To acquire practical solutions to these problems requires the use of metaheuristic approaches that trade completeness for...
Elsevier, 2005. — 552 p. This is a book about using fuzzy logic and evolutionary strategies — primarily genetic algorithms — to explore the structure of data, understand patterns in data, and create rule-based models from these patterns. As a general approach to exploring and modeling data, it is neither a book on data mining nor a book on expert or decision support systems....
Cham: Springer, 2022. — 230 p. This book presents a comparative perspective of current metaheuristic developments, which have proved to be effective in their application to several complex problems. The study of biological and social entities such as animals, humans, or insects that manifest cooperative behavior has produced several computational models in metaheuristic...
Springer, 2016. — 214. Evolutionary computation (EC) is one of the most important emerging technologies of recent times. Over the last years, there has been exponential growth of research activity in this field. Despite the fact that the concept itself has not been precisely defined, EC has become the standard term that encompasses several stochastic, population-based, and...
New York: Springer, 2017. — 236 p. This book compares the performance of various evolutionary computation (EC) techniques when they are faced with complex optimization problems extracted from different engineering domains. Particularly focusing on recently developed algorithms, it is designed so that each chapter can be read independently. Several comparisons among EC...
Springer, 2007. — 631 p. Evolutionary scheduling is a vital research domain at the interface of two important sciences - artificial intelligence and operational research. Scheduling problems are generally complex, large scale, constrained, and multi-objective in nature, and classical operational research techniques are often inadequate at solving them effectively. With the...
Kluwer Academic Publishers, 1987. — 256 p. — ISBN: 978-1-4612-9191-6. Concurrent data structures simplify the development of concurrent programs by encapsulating commonly used mechanisms for synchronization and communication into data structures. This thesis develops a notation for describing concurrent data structures, presents examples of concurrent data structures, and...
Springer, 2016. — 1319 p. The book is a collection of high-quality peer-reviewed research papers presented in the first International Conference on International Conference on Artificial Intelligence and Evolutionary Computations in Engineering Systems (ICAIECES -2015) held at Velammal Engineering College (VEC), Chennai, India during 22 – 23 April 2015. The book discusses wide...
Springer, 2017. — 842 p. The volume is a collection of high-quality peer-reviewed research papers presented in the International Conference on Artificial Intelligence and Evolutionary Computation in Engineering Systems (ICAIECES 2016) held at SRM University, Chennai, Tamilnadu, India. This conference is an international forum for industry professionals and researchers to...
Springer, 2016. — 294. Swarm-based algorithms have become one of the foremost researched and applied heuristics in the field of evolutionary computation within the past decade. One of the new and novel approaches is that of the self-organizing migrating algorithm (SOMA). Initially developed and published in 2001 by Prof. Ivan Zelinka, SOMA has been actively researched by a...
New York: InTech, 2012. — 299 p. Simulated Annealing is a probabilistic meta-heuristic that is based on statistical mechanics: while at high temperatures molecules in a liquid move freely, the slow reduction of temperature decreases the thermal mobility of the molecules. The final state forms a pure crystal which also corresponds to a state of minimum energy.
Boca Raton: CRC Press, 2023. — 147 p. This book systematically explores soft computing techniques starting from their initial stage to recent developments in this area. The book presents a survey of the existing knowledge and the current state-of-the-art development through cutting-edge original new contributions from the researchers. Soft Computing: Recent Advances and...
Singapore: Springer, 2023. — 254 p. This book provides fundamental concepts related to various types of genetic algorithms and practical applications in various domains such as medical imaging, manufacturing, and engineering design. The book discusses genetic algorithms which are used to solve a variety of optimization problems. The genetic algorithms are demonstrated to offer...
Bentham Books, 2023. — 155 p. This book presents research focused on the design of fractal antennas using bio-inspired computing techniques. The authors present designs for fractal antennas having desirable features like size reduction characteristics, enhanced gain, and improved bandwidths. The research is summarized in six chapters which highlight the important issues related...
Springer Nature Switzerland AG, 2020. — xii, 506 p. — (Natural Computing Series). This edited book reports on recent developments in the theory of evolutionary computation, or more generally the domain of randomized search heuristics. It starts with two chapters on mathematical methods that are often used in the analysis of randomized search heuristics, followed by three...
IEEE/John Wiley, 2014. — 238 p. Recent advances in wireless and mobile technologies make communication possible anywhere and anytime with any device ranging from smartphones, tablets, to vehicles. We can envision a wide range of applications where the deployment of these ad hoc networks is key; for example, in remote locations coordinating the evacuation and rescue of people...
InTech, 2009, -582 p. This book presents several recent advances on Evolutionary Computation, specially evolution-based optimization methods and hybrid algorithms for several applications, from optimization and learning to pattern recognition and bioinformatics. Concerning evolutionbased optimization methods, this book presents diverse versions of genetic algorithms, genetic...
Springer, 2003. — 202 p. Embedded system design is one of the fastest growing markets and automatic tools have to be developed to help the designer during the construction process. Even single chips can contain up to several million transistors and on the system level it even becomes worse. For the designer it is desirable to have a so-called "push button" tool, that supports...
Springer, 2010. — 349 p. 13th European Conference, EuroGP 2010, Istanbul, Turkey, April 7-9, 2010, Proceedings. The wide range of topics in this volume reflect the current state of research in the field, including representations, theory, operators and analysis, novel models, performance enhancements, extensions of genetic programming, and various applications. The volume...
IEEE Press/John Wiley, 2006, -292 p. Ten years have elapsed since the first publication of this book. In that decade of time, evolutionary computation has matured from a fringe element of computer science to a well-recognized serious endeavor. Although specific numbers are difficult to estimate, it would not be unreasonable to believe that over 10,000 papers have now been...
Springer, 2003. — 824 p. Second International Conference, EMO 2003, Faro, Portugal, April 8-11, 2003, Proceedings. This book constitutes the refereed proceedings of the Second International Conference on Evolutionary Multi-Criterion Optimization, EMO 2003, held in Faro, Portugal, in April 2003. The 56 revised full papers presented were carefully reviewed and selected from a...
Springer, 2009. — 599 p. 5th International Conference, EMO 2009, Nantes, France, April 7-10, 2009, Proceedings. 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...
Springer, 2002. — 347 p. 5th European Conference, EuroGP 2002, Kinsale, Ireland, April 3-5, 2002. Proceedings. This volume records the proceedings of the Fifth European conference on Genetic Programming (EuroGP 2002) which took place in Kinsale, Ireland on April3–5, 2002, continuing an established tradition of yearly meetings among the most prominent researchers on Genetic...
Springer, 2002. — 272 p. This book addresses the integration of two areas of computer science, namely data mining and evolutionary algorithms. Both these areas have become increasingly popular in the last few years, and their integration is currently an area of active research. In essence, data mining consists of extracting valid, comprehensible, and interesting knowledge from...
Cham: Springer International Publishing, 2019. — 322 p. — ISBN: 978-3-030-10752-9. This open access book is the final publication of the COST Action IC1303 Algorithms, Architectures and Platforms for Enhanced Living Environments (AAPELE) project. Ambient Assisted Living (AAL) is an area of research based on Information and Communication Technologies (ICT), medical research, and...
Springer, 2015. — 466 p. 8th International Conference, EMO 2015, Guimarães, Portugal, March 29 - April 1, 2015. Proceedings, Part I. This book constitutes the refereed proceedings of the 8th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2015 held in Guimarães, Portugal in March/April 2015. The 68 revised full papers presented together with 4 plenary...
Springer, 2015. — 603 p. 8th International Conference, EMO 2015, Guimarães, Portugal, March 29 - April 1, 2015. Proceedings, Part II. This book constitutes the refereed proceedings of the 8th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2015 held in Guimarães, Portugal in March/April 2015. The 68 revised full papers presented together with 4...
John Wiley, 2000. — 511 p. In the past decade, the study of how to apply genetic algorithms to problems in the industrial engineering world has been a subject engaging the curiosity of many researchers and practitioners in the area of management science, operations research, and industrial and systems engineering. A major reason for this interest is that genetic algorithms are...
Springer, 2003. — 1001. The term evolutionary computing refers to the study of the foundations and applications of certain heuristic techniques based on the principles of natural evolution; thus the aim of designing evolutionary algorithms (EAs) is to mimic some of the processes taking place in natural evolution. These algorithms are classified into three main categories,...
Springer, 2009. — 396 p. 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...
Springer, 2009. — 269 p. 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...
Scitech Publishing, 2021. — 342 p. — ISBN: 978-1785615528. Several evolutionary algorithms (EAs) have emerged in recent decades that mimic the behaviour and evolution of biological entities. EAs are widely used to solve single and multi-objective optimization engineering problems. EAs have also been applied to a variety of microwave components, antenna design, radar design, and...
Springer, 2005, -339 p. The last decade of the 20th century has witnessed a surge of interest in numerical, computation-intensive approaches to information processing. The lines that draw the boundaries among statistics, optimization, artificial intelligence and information processing are disappearing, and it is not uncommon to find well-founded and sophisticated mathematical...
MDPI, 2022. — 316 p. — ISBN: 978-3-0365-2715-4. Evolutionary algorithms (EAs) are population-based global optimizers, which, due to their characteristics, have allowed us to solve, in a straightforward way, many real-world optimization problems in the last three decades, particularly in engineering fields. Their main advantages are the following: they do not require any...
BPB Publications, 2021 — 270 p. — ISBN: 8194837758. Refuel your AI Models and ML applications with High-Quality Optimization and Search Solutions. Key Features Complete coverage on the practical implementation of genetic algorithms. Intuitive explanations and visualizations supply theoretical concepts. Added examples and use-cases on the performance of genetic algorithms. Use...
Springer, 2007. — 409 p. Evolutionary computation has become an important problem solving methodology among many researchers working in the area of computational intelligence. The population-based collective learning process, self-adaptation, and robustness are some of the key features of evolutionary algorithms when compared to other global optimization techniques....
Apple Academic Press, 2016. — 624 p. — ISBN: 1771883367. Edited by professionals with years of experience, this book provides an introduction to the theory of evolutionary algorithms and single- and multi-objective optimization, and then goes on to discuss to explore applications of evolutionary algorithms for many uses with real-world applications. Edited by professionals with...
Springer, 2019. — 109 p. — (Adaptation, Learning, and Optimization 21). — ISBN: 978-3-030-02728-5. 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....
Springer, 2013. — 185 p. This original and timely monograph describes a unique self-contained excursion that reveals to the readers the roles of two basic cognitive abilities, i.e. intention recognition and arranging commitments, in the evolution of cooperative behavior. This book analyses intention recognition, an important ability that helps agents predict others’ behavior,...
Springer, 2005. — 405 p. 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...
John Wiley, 2004,-272 p. When we agreed to edit this book for a second edition, we looked forward to a bit of updating and including some of our latest research results. However, the effort grew rapidly beyond our original vision. The use of genetic algorithms (GAs) is a quickly evolving field of research, and there is much new to recommend. Practitioners are constantly...
2nd ed. — 1998. — 253 p. Introduction to Optimization Finding the Best Solution What Is Optimization? Root Finding versus Optimization Categories of Optimization Minimum-Seeking Algorithms Exhaustive Search Analytical Optimization Nelder-Mead Downhill Simplex Method Optimization Based on Line Minimization Natural Optimization Methods Biological Optimization: Natural Selection...
Springer, 2016. — 320 p. 19th European Conference, EuroGP 2016, Porto, Portugal, March 30 - April 1, 2016, Proceedings. This book constitutes the refereed proceedings of the 19th European Conference on Genetic Programming, EuroGP 2016, held in Porto, Portugal, in March/April 2016 co-located with the Evo*2016 events: EvoCOP, EvoMUSART, and EvoApplications. The 11 revised full...
CRC Press, 2009. — 349 p. — (International Series on Computational Intelligence). — ISBN: 1439803692, 9781439803691 What do financial data prediction, day-trading rule development, and bio-marker selection have in common? They are just a few of the tasks that could potentially be resolved with genetic programming and machine learning techniques. Written by leaders in this...
Springer, 2020. — 437 p. — ISBN: 978-981-15-3685-4. This book delivers the state of the art in Deep Learning (DL) methods hybridized with evolutionary computation (EC). Over the last decade, DL has dramatically reformed many domains: computer vision, speech recognition, healthcare, and automatic game playing, to mention only a few. All DL models, using different architectures...
Morgan Kaufmann, 2001. — 587. Evolution in nature, an outstanding example of natural adaptation processes at work, has resulted in a fantastic diversity of life-forms with amazing capabilities. Populations of organisms, adapting to their particular environmental conditions, form cooperating and competing teams in an evolutionary interplay of selection and variation mechanisms....
Springer, 2022. — 277 p. — (Engineering Optimization: Methods and Applications). — ISBN13: 9789811946325. — ISBN10: 9811946329. This book covers the latest advances in Cultural Algorithms, their general framework, different variants, hybridized versions with other meta-heuristic and search techniques, and their applications. Cultural Algorithms (CAs) are meta-heuristic...
Springer, 2013. — 262 p. The analysis of evolutionary algorithms is a lively and very active field of research. Many different and tremendously useful tools and methods for analyzing evolutionary algorithms have been and continue to be developed. In this book, an introduction to this field of research is presented that makes it accessible by introducing the most important and...
Educohack Press, 2025. — 298 p. "Python-Based Evolutionary Algorithms for Engineers" is a comprehensive guide designed to empower engineers with the knowledge and skills needed to harness the power of evolutionary algorithms in optimization tasks. We seamlessly integrate theoretical foundations with hands-on implementation, making it accessible to both beginners and seasoned...
Springer, 2005. — 543 p. This carefully edited book puts together the state-of-the-art and recent advances in knowledge incorporation in evolutionary computation within a unified framework. The book provides a comprehensive self-contained view of knowledge incorporation in evolutionary computation including a concise introduction to evolutionary algorithms as well as knowledge...
Book, 256 p, The MIT Press, Cambridge, Massachusetts, London, England, Includes bibliographical references and indexes, ISBN: 0-262-04194-4 Basic Evolutionary Processes EV: A Simple Evolutionary System EV on a Simple Fitness Landscape EV on aMore Complex Fitness Landscape Evolutionary Systems as ProblemSolvers Exercises A Historical Perspective Early Algorithmic Views The...
Springer, 2001. — 495. During the first week of September 1999, the Second EvoNet Summer School on Theoretical Aspects of Evolutionary Computing was held at the Middelheim campus of the University of Antwerp, Belgium. Originally intended as a small get-together of Ph.D. students interested in the theory of evolutionary computing, the summer school grew to become a successful...
Palgrave Macmillan, Springer, 2019. — 125 p. — ISBN: 978-3-030-31921-2. This book analyses the changes to the regulation of everyday life that have taken place as a result of datafication, the ever-growing analytical, predictive, and structuring role of algorithms, and the prominence of the platform economy. Introduction: I’ll Be Watching You… Data: The Premise of New...
IGI Global, 2021. — xii+262 p. — ISBN13: 9781799841050; ISBN10: 1799841057. Genetic algorithms (GAs) are based on Darwin’s theory of natural selection and survival of the fittest. They are designed to competently look for solutions to big and multifaceted problems. Genetic algorithms are wide groups of interrelated events with divided steps. Each step has dissimilarities, which...
Springer, 2004. — 425 p. 7th European Conference, EuroGP 2004, Coimbra, Portugal, April 5-7, 2004, Proceedings. This book constitutes the refereed proceedings of the 7th European Conference on Genetic Programming, EuroGP 2004, held in Coimbra, Portugal, in April 2004. The 38 revised papers presented were carefully reviewed and selected from 61 submissions. The papers deal with...
Springer, 2005. — 393 p. 8th European Conference, EuroGP 2005, Lausanne, Switzerland, March 30-April 1, 2005, Proceedings. In this volume we present the contributions for the 18th European Conference on Genetic Programming (EuroGP 2005). The conference took place from 30 March to 1 April in Lausanne, Switzerland. EuroGP is a well-established conf- ence and the only one...
InTech, 2011. — 596 p. — ISBN: 9789533071718. Evolutionary algorithms (EAs) are the population-based metaheuristic optimization algorithms. Candidate solutions to the optimization problem are defined as individuals in a population, and evolution of the population leads to finding bett er solutions. The fitness of individuals to the environment is estimated and some mechanisms...
CRC Press, 2010. — 151. Structural health monitoring has become a growing R&D area, as witnessed by the increasing number of relevant journal and conference papers. Rapid advances in instrumentation and computational capabilities have led to a new generation of sensors, data communication devices and signal processing software for structural health monitoring. To this end, a...
Springer, 2012. — 203 p. One of the most challenging issues in modeling today's large-scale computational systems is to effectively manage highly parametrised distributed environments such as computational grids, clouds, ad hoc networks and P2P networks. Next-generation computational grids must provide a wide range of services and high performance computing infrastructures....
InTech, 2010, -326 p. Evolutionary computation has been widely used in computer science for decades. Even though it started as far back as the 1960s with simulated evolution, the subject is still evolving. During this time, new metaheuristic optimization approaches, like evolutionary algorithms, genetic algorithms, swarm intelligence, etc., were being developed and new fields...
InTech, 2008, -476 p. With the recent trends towards massive data sets and significant computational power, combined with evolutionary algorithmic advances evolutionary computation is becoming much more relevant to practice. Aim of the book is to present recent improvements, innovative ideas and concepts in a part of a huge EA field. Part I: Foundations and New Methods Limit...
MIT Press, 1994. — 769. Genetic Programming: On the Programming of Computers by Means of Natural Selection proposed a possible answer to the following question, attributed to Arthur Samuel in the 1950s: How can computers learn to solve problems without being explicitly programmed? In other words, how can computers be made to do what is needed to be done, without being told...
Cambridge: The MIT Press, 1998. - 609 p. Genetic programming may be more powerful than neural networks and other machine learning techniques, able to solve problems in a wider range of disciplines. In this ground-breaking book, John Koza shows how this remarkable paradigm works and provides substantial empirical evidence that solutions to a great variety of problems from many...
Book, 813 p,The MIT Press,Cambridge, Massachusetts London, England,ISBN: 0-262-11170-5 Introduction and Overview Pervasiveness of the Problem of Program Induction Introduction to Genetic Algorithms The Representation Problem for Genetic Algorithms Overview of Genetic Programming Detailed Description of Genetic Programming Four Introductory Examples of Genetic Programming Amount...
Springer Science+Business Media, Inc. 2003. 606 p. Background on Genetic Programming Automatic Synthesis of Controllers Automatic Synthesis of Circuits Automatic Synthesis of Circuit Topology, Sizing, Placement, and Routing Automatic Synthesis of Antennas Automatic Synthesis of Genetic Networks Automatic Synthesis of Metabolic Pathways Automatic Synthesis of Parameterized...
Springer, 2013. — 287 p. 16th European Conference, EuroGP 2013, Vienna, Austria, April 3-5, 2013, Proceedings. This book constitutes the refereed proceedings of the 16th European Conference on Genetic Programming, EuroGP 2013, held in Vienna, Austria, in April 2013 co-located with the Evo* 2013 events, EvoMUSART, EvoCOP, EvoBIO, and EvoApplications. The 18 revised full papers...
New York: Springer, 2022. — 389 p. This book addresses and disseminates state-of-the-art research and development of differential evolution (DE) and its recent advances, such as the development of adaptive, self-adaptive, and hybrid techniques. Differential evolution is a population-based meta-heuristic technique for global optimization capable of handling non-differentiable,...
Report, University of Illinois at Urbana-Champaign, Urbana IL 61801, 15 p, June 5, 2007 This report provides documentation for the general purpose genetic algorithm toolbox for MatLAB in C++. The fitness function used in the toolbox is written in MatLAB. The toolbox provides different selection, recombination, mutation, niching, and constraint-handling operators. Problems with...
Springer, 2009. — 249 p. The development of intellectual systems connecting the human brain and computer technologies represents one of the most important problems of the 21st century. Therefore analytical methods of data mining of computer databases are being developed. Intellectual behavior of technical objects as well as the biological ones is defined by their structure,...
Springer, 2002. — 363. DIMACS Workshop, Princeton, January 1999 The study of the genetic basis for evolution has flourished in this century, as well as our understanding of the evolvability and programmability of biological systems. Genetic algorithms meanwhile grew out of the realization that a computer program could use the biologically-inspired processes of mutation,...
Springer, 2002. — 265 p. Genetic programming (GP) has been highly successful as a technique for getting computers to automatically solve problems without having to tell them explicitly how to do it. Since its inception more than ten years ago genetic programming has been used to solve practical problems but along with this engineering approach there has been interest in how and...
Springer, 2002. — 398. The study and use of heuristic techniques for optimization have been successfully developed during the last decade. Among these techniques, Evolutionary Computation -Genetic Algorithms, Evolution Strategies, Evolutionary Programming and Genetic Programming- has been the reference. This book is devoted to a new paradigm for Evolutionary Computation, named...
CRC, 2017. — 304 p. — ISBN: 978-1138032316. The goal of this book is to understand the contributions in concrete areas such as framework efficiency variability factors and query variability factors to overall retrieval variability. Information retrieval process begins when a user enters a query into the system. For effectively retrieving relevant documents by IR strategies, the...
New York: Springer, 2019. — 156 p. Figures Tables The Basic Evolutionary Algorithm Differential Evolution Basic Concepts Important Variants Potential Future Research Directions Memetic Algorithm Particle Swarm Optimization Studies on PSO Multi-objective Evolutionary Algorithm Basic Concepts and Notations of Networks Network Topology Modularity Power Law Degree Distribution...
Springer, 2023. — 535 p. — ISBN13: 9783031116858. — ISBN10: 3031116852. This handbook distills the wealth of expertise and knowledge from a large community of researchers and industrial practitioners in Software Product Lines (SPLs) gained through extensive and rigorous theoretical, empirical, and applied research. It is a timely compilation of well-established and cutting-edge...
Springer, 2006. — 306. Estimation of Distribution Algorithms (EDAs) are a set of algorithms in the Evolutionary Computation (EC) field characterized by the use of explicit probability distributions in optimization. Contrarily to other EC techniques such as the broadly known Genetic Algorithms (GAs) in EDAs, the crossover and mutation operators are substituted by the sampling of...
ISBN: 978-3-642-22083-8. Springer 2011. This book is the result of several years of research trying to better characterize parallel genetic algorithms (pGAs) as a powerful tool for optimization, search, and learning. We here offer a presentation structured in three parts. The first one is tar- geted to the algorithms themselves, discussing their components, the physical...
Wiley-ISTE, 2016. — 182 p. — ISBN: 1848218133, 9781848218130 Researchers and practitioners in food science and technology routinely face several challenges, related to sparseness and heterogeneity of data, as well as to the uncertainty in the measurements and the introduction of expert knowledge in the models. Evolutionary algorithms (EAs), stochastic optimization techniques...
Wiley ISTE, 2017. — 334 p. — (Computer engineering series. Metaheuristics Set). — ISBN10: 1848218079. Evolutionary computation algorithms are employed to minimize functions with large number of variables. Biogeography-based optimization (BBO) is an optimization algorithm that is based on the science of biogeography, which researches the migration patterns of species. These...
Springer, 2015. — 240 p. 18th European Conference, EuroGP 2015, Copenhagen, Denmark, April 8-10, 2015, Proceedings. This book constitutes the refereed proceedings of the 18th European Conference on Genetic Programming, EuroGP 2015, held in Copenhagen, Spain, in April 2015 co-located with the Evo 2015 events, EvoCOP, Evo MUSART and Evo Applications. The 12 revised full papers...
Springer, 1997, -226 p. The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. The rapid development of control technology impacts all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new applications, new philosophies, new challenges. Much of...
USA: IGI Global, Engineering Science Reference, 2020. — 344 p. — (Advances in Mechatronics and Mechanical Engineering). — ISBN: 9781799819202. "This book explores the use of genetic algorithms in the context of the analysis of remotely sensed images. This is illustrated with a case study of the M370 crash" The tragic disappearance of the Malaysia Airlines Flight MH370 has...
Morgan Kaufmann, 2001. — 342 p. — ISBN: 978-1558607347. Foundations of Genetic Algorithms, Volume 6 is the latest in a series of books that records the prestigious Foundations of Genetic Algorithms Workshops, sponsored and organised by the International Society of Genetic Algorithms specifically to address theoretical publications on genetic algorithms and classifier systems....
Springer, 1996. — 162 p. Production scheduling dictates highly constrained mathematical models with complex and often contradicting objectives. Evolutionary algorithms can be formulated almost independently of the detailed shaping of the problems under consideration. As one would expect, a weak formulation of the problem in the algorithm comes along with a quite inefficient...
Springer, 2011, -298 p. Clustering is an important unsupervised classification technique where a set of patterns, usually vectors in multidimensional space, are grouped into clusters based on some similarity or dissimilarity criteria. In crisp clustering, each pattern is assigned to exactly one cluster, whereas in fuzzy clustering, each pattern is given a membership degree to...
Intelliz Press, 2021. — 302 p. A genetic algorithm (GA) is a search and optimization method that works by mimicking the evolutionary principles and chromosomal processing in natural genetics. The genetic algorithm is a multi-path algorithm that searches many peaks in parallel, hence reducing the possibility of local minimum trapping and solving the multi-objective optimization...
Springer, 2017. — 369 p. 20th European Conference, EuroGP 2017, Amsterdam, The Netherlands, April 19-21, 2017, Proceedings. This book constitutes the refereed proceedings of the 20th European Conference on Genetic Programming, EuroGP 2017, held in Amsterdam, The Netherlands, in April 2017, co-located with the Evo* 2017 events, EvoCOP, EvoMUSART, and EvoApplications. The 14...
John Wiley, 1999. — 500. This book collects the papers of the invited lecturers of EUROGEN99, the Short Course on Evolutionary Algorithms in Engineering and Computer Science, held at the University of Jyvaskyla, Finland, between May 30 and June 3, 1999. In addition, this book contains several industrial presentations given during the Short Course by contributors belonging to...
Springer, 2001. — 393 p. 4th European Conference, EuroGP 2001 Lake Como, Italy, April 18–20, 2001 Proceedings. In this volume are the proceedings of the fourth European conference on Genetic Programming (EuroGP 2001) which took place at Lake Como in Italy on April, 18–20 2001. EuroGP has become firmly established as the premier European event devoted to Genetic Programming....
Cham: Springer International Publishing, 2019. — 304 p. — ISBN: 978-3-030-03131-2. This book is intended to provide a systematic overview of so-called smart techniques, such as nature-inspired algorithms, machine learning and metaheuristics. Despite their ubiquitous presence and widespread application to different scientific problems, such as searching, optimization and /or...
Springer Singapore 2022. — 279 p. — ISBN: 978-3-031-07512-4. The introduction of nature-inspired optimization algorithms (NIOAs), over the past three decades, helped solve nonlinear, high-dimensional, and complex computational optimization problems. NIOAs have been originally developed to overcome the challenges of global optimization problems such as nonlinearity,...
Springer, 2012. — 289 p. 15th European Conference, EuroGP 2012, Málaga, Spain, April 11-13, 2012, Proceedings. This book constitutes the refereed proceedings of the 15th European Conference on Genetic Programming, EuroGP 2012, held in Málaga, Spain, in April 2012 co-located with the Evo* 2012 events. The 18 revised full papers presented together with 5 poster papers were...
Springer, 2006. — 213 p. Evolutionary algorithms and their related computations are solver systems which use computational models inspired in Darwinian natural selection processes as a key element in their design and implementation. In general, evolutionary computation (EC) is used to solve NP-hard problems which cannot be solved with other tools because of their intrinsic...
Springer, 2012. — 395 p. 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...
Springer, 2014. — 257 p. 17th European Conference, EuroGP 2014, Granada, Spain, April 23-25, 2014, Revised Selected Papers. The book constitutes the refereed proceedings of the 17th European Conference on Genetic Programming, Euro GP 2014, held in Grenada, Spain, in April 2014 co-located with the Evo*2014 events, Evo BIO, Evo COP, Evo MUSART and Evo Applications. The 15 revised...
Springer, 2003. — 157. Since man began to dream of machines that could automate not only the more mundane and laborious tasks of everyday life, but that could also improve some of the more agreeable aspects, he has turned to nature for inspiration. This inspiration has taken all sorts of forms, with inventors producing everything from Icarus-like, bird-inspired flying machines...
Springer, 2007. — 971 p. 4th International Conference, EMO 2007, Matsushima, Japan, March 5-8, 2007, Proceedings. Multicriterion optimization refers to problems with two or more objectives (normally in conflict with each other) which must be simultaneously satisfied. Evolutionary algorithms have been used for solving multicriterion optimization problems for over two decades,...
CRC Press, 2022. — 140 p. — ISBN: 978-1-032-02473-8. The use of metaheuristic algorithms (MA) has been increasing in recent years, and the image processing field is not exempted from their application. In the last two years, a big amount of MA has been introduced as alternatives for solving complex optimization problems. This book collects the most prominent MA of 2019 and 2020...
Springer, 2008. — 384 p. 11th European Conference, EuroGP 2008, Naples, Italy, March 26-28, 2008, Proceedings. The 11th European Conference on Genetic Programming, EuroGP 2008, took place in Naples, Italy from 26 to 28 March in the University of Naples Congress Centre with spectacular views over the Gulf of Naples. This volume contains the papers for the 21 oral presentations...
Springer, 2022. — 580 p. — ISBN: 978-3-030-. This open-access book provides a comprehensive view of data ecosystems and platform economics from methodical and technological foundations up to reports from practical implementations and applications in various industries. To this end, the book is structured in four parts: Part I “Foundations and Contexts” provides a general...
Springer, 2010, -197 p. Data mining is a very active research area with many successful real-world applications. It consists of a set of concepts and methods used to extract interesting or useful knowledge (or patterns) from real-world datasets, providing valuable support for decision making in industry, business, government, and science. Although there are already many types...
CRC Press, 2025. — 215 p. — (Advances in Metaheuristics). — ISBN: 978-1-032-89138-5. In the rapidly evolving domain of computational problem-solving, this book delves into the cutting-edge Automatic Generation of Algorithms (AGA) paradigm, a groundbreaking approach poised to redefine algorithm design for optimization problems. Spanning combinatorial optimization, machine...
The MIT Press, 2001. — 491 p. Among the first uses of the computer was the development of programs to model perception, reasoning, learning, and evolution. Further developments resulted in computers and programs that exhibit aspects of intelligent behavior. The field of artificial intelligence is based on the premise that thought processes can be computationally modeled....
Springer, 1997. — 324 p. As of today, Evolutionary Computing and Fuzzy Set Computing are two mature, wen -developed, and higbly advanced technologies of information processing. Bach of them has its own clearly defined research agenda, specific goals to be achieved, and a wen setUed algorithmic environment. Concisely speaking, Evolutionary Computing (EC) is aimed at a coherent...
Springer, 2005. — 181 p. A black-box optimization problem may be defined by specifying (1) a set of all potential solutions to the problem and (2) a measure for evaluating the quality of each candidate solution. The task is to find a solution or a set of solutions that perform best with respect to the specified measure. An important feature of black-box optimization is that a...
Wiley-ISTE, 2017. — 274 p. — ISBN: 978-1848218048. 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...
Ph.D. Thesis, School of Electrical, Electronic and Computer Engineering,University of Western May 2008, 281 p The Genetic Programming paradigm, which applies the Darwinian principle of evolution to hierarchical computer programs, has produced promising breakthroughs in various scientific and engineering applications. However, one of the main drawbacks of Genetic Programming has...
Springer, 2000. — 370 p. European Conference, EuroGP 2000 Edinburgh, Scotland, UK, April 15-16, 2000 Proceedings. This volume contains the proceedings of EuroGP 2000, the European Conf- ence on Genetic Programming, held in Edinburgh on the 15th and 16th April 2000. This event was the third in a series which started with the two European workshops: EuroGP’98, held in Paris in...
Lulu Enterprises, 2008. - 252 p. - ISBN10: 1409200736 Genetic programming (GP) is a systematic, domain-independent method for getting computers to solve problems automatically starting from a high-level statement of what needs to be done. Using ideas from natural evolution, GP starts from an ooze of random computer programs, and progressively refines them through processes of...
Springer, 1999. — 293 p. Second European Workshop, EuroGP'99, Göteborg, Sweden, May 26-27, 1999, Proceedings. This book constitutes the refereed proceedings of the Second European Workshop on Genetic Programming, EuroPG '99, held in Göteborg, Sweden in May 1999. The 12 revised full papers and 11 posters presented have been carefully reviewed and selected for inclusion in the...
InTech, 2012. - 328 p. Genetic Algorithms (GAs) are global optimization techniques used in many real-life applications. They are one of several techniques in the family of Evolutionary Algorithms – algorithms that search for solutions to optimization problems by evolving better and better solutions. A Genetic Algorithm starts with a population of possible solutions for the...
Springer, 2015. — 206 p. What is this book about? The field of multimodal optimization is just forming, but of course it has its roots in many older works, namely niching, parallel evolutionary algorithms, and global optimization. My aim is to bring all these together and thereby help to shape the field by collecting use cases, algorithms, and performance measures. In my view,...
Springer, 2013. — 859 p. 7th International Conference, EMO 2013, Sheffield, UK, March 19-22, 2013. Proceedings. This book constitutes the refereed proceedings of the 7th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2013 held in Sheffield, UK, in March 2013. The 57 revised full papers presented were carefully reviewed and selected from 98...
Morgan Kaufmann, 1991. — 341 p. — ISBN: 978-1558601703. Foundations of Genetic Algorithms 1991 (FOGA 1) discusses the theoretical foundations of genetic algorithms (GA) and classifier systems. This book compiles research papers on selection and convergence, coding and representation, problem hardness, deception, classifier system design, variation and recombination,...
Hershey: IGI Global, 2021. — 1569 p. Genetic programming is a new and evolutionary method that has become a novel area of research within artificial intelligence known for automatically generating high-quality solutions to optimization and search problems. This automatic aspect of the algorithms and the mimicking of natural selection and genetics makes genetic programming an...
Springer, 2001. — 185 p. The book is dedicated to the use of genetic algorithms in theoretical economic research. Genetic algorithms offer the chance of overcoming the limitations traditional mathematical tractability puts on economic research and thus open new horzions for economic theory. The book reveals close relationships between the theory of economic learning via genetic...
Hampshire College, Division III thesis, May 2001, 127 p The push language and pushgp Pushgp compared to gp2 with adfs Variations in genetic operators New ground – evolving factorial Linear coded genetic programming in Java Ljgp user’s guide Ljgp applied Computational effort – lisp code Genetic programming systems in Java Ljgp/Java-vm benchmarks
InTech, 2012, -376 p. Genetic Algorithms are a part of Evolutionary Computing, which is a rapidly growing area of Artificial Intelligence. The popularity of Genetic Algorithms is reflected in the increasing amount of literature devoted to theoretical works and real-world applications in both scientific and engineering areas. The useful application and the proper combination of...
Springer, 2000. — 150 p. Automatic Re-engineering of Software Using Genetic Programming describes the application of Genetic Programming to a real world application area - software re-engineering in general and automatic parallelization specifically. Unlike most uses of Genetic Programming, this book evolves sequences of provable transformations rather than actual programs. It...
Springer, 2003. — 498 p. 6th European Conference, EuroGP 2003, Essex, UK, April 14-16, 2003. Proceedings. In this volume we present the accepted contributions to the Sixth European Conference on Genetic Programming (EuroGP 2003) which took place at the University of Essex, UK on 14-16 April 2003. EuroGP is now a well-established conference and, without any doubt, the most...
Springer International Publishing, 2018. — 497 p. This handbook offers a comprehensive treatise on Grammatical Evolution (GE), a grammar-based Evolutionary Algorithm that employs a function to map binary strings into higher-level structures such as programs. GE's simplicity and modular nature make it a very flexible tool. Since its introduction almost twenty years ago,...
Philadelphia: SIAM, 2002. - 164 p. Simulated annealing has proved to be an easy and reliable method for finding optimal values of a problem in cases where there is no road map to possible solutions. Facts, Conjectures, and Improvements for Simulated Annealing offers an introduction to this topic for novices and provides an informative review of the area for the more expert...
World Scientific, 1997. — 252 p. Ever since fuzzy logic was introduced by Lotfi Zadeh in the mid-sixties and genetic algorithms by John Holland in the early seventies, these two fields widely been subjects of academic research the world over. During the last few years, they have been experiencing extremely rapid growth in the industrial world, where they have been shown to be...
Springer, 2012. — 136 p. Let the experts of EAs show industrial engineers and operators what EAs can do! The current book makes exactly this by presenting a collection of real significant industrial problems and their EA-based solutions. The considered case studies help the reader learn to employ EAs with a minimal investment in time and effort. This is what makes the current...
Springer, 2010. — 293 p. — ISBN: 978-3642134241, e-ISBN: 978-3642134258. Series: Adaptation, Learning, and Optimization (Book 5). The performance of Evolutionary Algorithms can be enhanced by integrating the concept of agents. Agents and Multi-agents can bring many interesting features which are beyond the scope of traditional evolutionary process and learning. This book...
Springer, 2012. — 247 p. This book focuses on the analysis and application of Markov networks, and undirected models in general, as probabilistic models in EDAs. Markov networks are not merely a different alternative to directed PGMs. They support a number of attributes that make them particularly suitable in the context of evolutionary optimisation. In contrast to Bayesian...
Springer, 2019. — 355 p. — (EAI/Springer Innovations in Communication and Computing). — ISBN: 978-3-319-96450-8. Automatic Generation of Cyber Architectures Optimized for Security, Cost, and Mission Performance: A Nature-Inspired Approach Optimizing Resource Allocation of Wireless Networks with Carrier Aggregation Using Evolutionary Programming Artificial Feeding Birds (AFB): A...
Springer, 2011. — 360 p. 14th European Conference, EuroGP 2011, Torino, Italy, April 27-29, 2011, Proceedings. This book constitutes the refereed proceedings of the 14th European Conference on Genetic Programming, EuroGP 2011, held in Torino, Italy, in April 2011 co-located with the Evo* 2011 events. This 20 revised full papers presented together with 9 poster papers were...
Wiley, 2013. — 776 p. — ISBN: 0470937416, 9780470937419 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...
Springer, 1997, -204 p. Natural evolution has "created" a multitude of systems in which the actions of simple, locally-interacting components give rise to coordinated global information processing. Insect colonies, cellular assemblies, the retina, and the immune system, have all been cited as examples of systems in which emergent computation occurs. This term refers to the...
Springer, 2000. — 223 p. The main theme of the book is as follows. First, a static, component-wise analysis of recombination and mutation is performed. This analysis highlights some of the strengths and weaknesses of both operators. For example, the analysis suggests that increasing the number of peaks in a fitness landscape (i.e., its multimodality) can have a highly...
Springer, 2007. — 216 p. — ISBN: 978-3540734796. Readers will find here a fascinating text that is the thoroughly refereed post-proceedings of the 9th Workshop on the Foundations of Genetic Algorithms, FOGA 2007, held in Mexico City in January 2007. The 11 revised full papers presented were carefully reviewed and selected during two rounds of reviewing and improvement from 22...
World Scientific, 2004. — 193 p. In this book, efficient and scalable coevolutionary algorithms for distributed, network-based decision-making, which utilize objective functions are developed in a networked environment where internode communications are a primary factor in system performance. A theoretical foundation for this class of coevolutionary algorithms is introduced...
N.-Y.: Springer, 2015(!). - 862 p. The book is a collection of high-quality peer-reviewed research papers presented in Proceedings of International Conference on Artificial Intelligence and Evolutionary Algorithms in Engineering Systems (ICAEES 2014) held at Noorul Islam Centre for Higher Education, Kumaracoil, India. These research papers provide the latest developments in the...
Springer, 2011. — 634 p. 6th International Conference, EMO 2011, Ouro Preto, Brazil, April 5-8, 2011, Proceedings. 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...
New York: Springer, 2005. - 296 p. Evolutionary multiobjective optimization is currently gaining a lot of attention, particularly for researchers in the evolutionary computation communities. Covers the authors’ recent research in the area of multiobjective evolutionary algorithms as well as its practical applications.
Springer, 2010. — 707 p. — ISBN: 978-3642107009, e-ISBN: 978-3642107016. Series: Adaptation, Learning, and Optimization (Book 2). In modern science and engineering, laboratory experiments are replaced by high fidelity and computationally expensive simulations. Using such simulations reduces costs and shortens development times but introduces new challenges to design...
Springer, 2005. - 199 p. This book does not try to cover real-life applications either. There have been many applications of structured EAs in many fields but our focus is on models, theory, and the empirical properties of structured EAs. The interested reader will find an abundant sampling of successful applications of spatially structured EAs in the proceedings volumes of...
Springer, 2017. — 717 p. 9th International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings. This book constitutes the refereed proceedings of the 9th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2017 held in Münster, Germany in March 2017. The 33 revised full papers presented together with 13 poster presentations were...
Springer, 2023. — 272 p. This book brings together some of the most impactful researchers in the field of Genetic Programming (GP), each one working on unique and interesting intersections of theoretical development and practical applications of this evolutionary-based Machine Learning paradigm. Topics of particular interest for this year`s book include powerful modeling...
Springer, 2013. — 454 p. Evolutionary algorithms (EAs) are generic heuristics that learn from natural collective behavior and can be applied to solve very difficult optimization problems. Applications include engineering problems, scheduling problems, routing problems, assignment problems, finance and investment problems, analyzing problems of complex social behavior, to state...
Springer, 2009. — 373 p. 12th European Conference, EuroGP 2009 Tübingen, Germany, April, 15-17, 2009 Proceedings. This book constitutes the refereed proceedings of the 11th European Conference on Genetic Programming, EuroGP 2009, held in Tübingen, Germany, in April 2009 colocated with the Evo 2009 events. The 21 revised plenary papers and 9 revised poster papers were carefully...
InTech, 2012, -298 p. Genetic programming (GP) is a branch of Evolutionary Computing that aims the automatic discovery of programs to solve a given problem. Since its appearance, in the earliest nineties, GP has become one of the most promising paradigms for solving problems in the artificial intelligence field, producing a number of human-competitive results and even...
Springer, 2016. — 199 p. — ISBN: 9783319338576 This book provides a comprehensive overview of the field of pattern mining with evolutionary algorithms. To do so, it covers formal definitions about patterns, patterns mining, type of patterns and the usefulness of patterns in the knowledge discovery process. As it is described within the book, the discovery process suffers from...
ITexLi, 2022. — 156 p. — ISBN: 180355178X 9781803551784 1803551771 9781803551777 1803551798 9781803551791. The solution to many real-world problems lies in optimizing processes, parameters, or techniques, which requires dealing with immense search spaces. As such, finding solutions involves exhaustive methods to evaluate all possible solutions in the search for a global...
Nova, 2015. — 234 p. A common approach for solving simulation-driven engineering problems is by using metamodel-assisted optimization algorithms, namely, in which a metamodel approximates the computationally expensive simulation and provides predicted values at a lower computational cost. Such algorithms typically generate an initial sample of solutions which are then used to...
Springer, 2004. — 182 p. EAs that constitute the evolutionary computation have emerged as the primary unifying principle of modem biological thought for global optimization. Classic Darwinian evolutionary theory, combined with the selectionism of Weismann and the genetics of Mendel, has now become a rather universally accepted set of arguments known as the neo-Darwinian...
Tutorial, Computer Science Department, Colorado State University, Statistics and Computing, 1994, 37 p. Encodings and Optimization Problems. How Hard is Hard? The Canonical Genetic Algorithm. Why does it work? Search Spaces as Hypercubes. Two Views of Hyperplane Sampling. The Schema Theorem. The Case for Binary Alphabets. Criticisms of the Schema Theorem. An Executable Model of...
Morgan Kaufmann, 1995. — 300 p. — ISBN: 978-1-55860-356-1. Foundations of Genetic Algorithms, 3 focuses on the principles, methodologies, and approaches involved in the integration of genetic algorithm into mainstream mathematics, as well as genetic operators, genetic programming, and evolutionary algorithms. The selection first offers information on an experimental design...
Springer, 2005, -325 p. The 8th Workshop on the Foundations of Genetic Algorithms, FOGA-8, was held at the University of Aizu in Aizu-Wakamatsu City, Japan, January 5–9, 2005. This series of workshops was initiated in 1990 to encourage further research on the theoretical aspects of genetic algorithms, and the workshops have been held biennially ever since. The papers presented...
Springer, 2000. — 145 p. — ISBN: 3-540-66939-6. This thesis develops an artificial life paradigm for computer graphics animation. Animals in their natural habitats have presented a long-standing and difficult challenge to animators. We propose a framework for achieving the intricacy of animal motion and behavior evident in certain natural ecosystems, with minimal animator...
Springer, 2007. — 613 p. This book provides a compilation on the state-of-the-art and recent advances of evolutionary algorithms in dynamic and uncertain environments within a unified framework. The motivation for this book arises from the fact that some degree of uncertainty in characterizing any realistic engineering systems is inevitable. Representative methods for...
Springer, 2013. — 479 p. This book provides a compilation on the state-of-the-art and recent advances of evolutionary computation for dynamic optimization problems. The motivation for this book arises from the fact that many real-world optimization problems and engineering systems are subject to dynamic environments, where changes occur over time. Key issues for addressing...
Springer, 2010, -433 p. This is a textbook on evolutionary algorithms (EAs). In preparing the proposal and the manuscript, the following questions were always kept in our minds. Is this book convenient for teaching, studying, and self-study, i.e., have the contents been arranged in a pedagogically sound way? Does this book introduce the state of the art of EAs? Does this book...
CRC Press, 2002. — 306 p. Many books on Evolutionary Computation, and, more specifically, on Genetic Algorithms, have already been published. When we decided to write a book on Evolutionary Electronics, we were basically motivated by what appears to be a turning point in this area: a wider range of applications in synthesis of engineering and control systems, being now tackled...
New York: Springer, 2019. — 361 p. Many machine learning tasks involve solving complex optimization problems, such as working on non-differentiable, non-continuous, and non-unique objective functions; in some cases it can prove difficult to even define an explicit objective function. Evolutionary learning applies evolutionary algorithms to address optimization problems in...
Springer, 2001. — 724 p. First International Conference, EMO 2001, Zurich, Switzerland, March 7-9, 2001 Proceedings. This book constitutes the refereed proceedings of the First International Conference on Multi-Criterion Optimization, EMO 2001, held in Zurich, Switzerland in March 2001. The 45 revised full papers presented were carefully reviewed and selected from a total of 87...
Springer, 2013. — 96 p. This book describes a real time control algorithm using Genetic Algorithm (GA) and Ant Colony Optimization (ACO) algorithm for optimizing PID controller parameters. Proposed method was tested on GUNT RT 532 Pressure Process Control System. The dynamic model of the process to be controlled was obtained using Artificial Neural Network (ANN). Using the...
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