New Developments in Evolutionary Computation Research

This book discusses research and new developments on evolutionary computation.

New Developments in Evolutionary Computation Research

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 train a preliminary metamodel and to initiate an optimization process. One approach for generating the initial sample is with the design of experiment methods which are statistically oriented, while the more recent search-driven sampling approach invokes a computational intelligence optimizer such as an evolutionary algorithm, and then uses the vectors it generated as the initial sample. This book discusses research and new developments on evolutionary computation.

Experimental Research in Evolutionary Computation

In W. Langdon (Ed.), GECCO 2002: Proceedings of the Genetic and Evolutionary Computation Conference (pp. 11–18). ... New developments in ranking and selection: An empirical comparison of the three main approaches.

Experimental Research in Evolutionary Computation

This book introduces the new experimentalism in evolutionary computation, providing tools to understand algorithms and programs and their interaction with optimization problems. It develops and applies statistical techniques to analyze and compare modern search heuristics such as evolutionary algorithms and particle swarm optimization. The book bridges the gap between theory and experiment by providing a self-contained experimental methodology and many examples.

New Achievements in Evolutionary Computation

However, even with so much work done, novel research into new techniques and new areas of usage is far from over. This book presents some new theoretical as well as practical aspects of evolutionary computation.

New Achievements in Evolutionary Computation

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 of usage in artificial intelligence, machine learning, combinatorial and numerical optimization, etc., were being explored. However, even with so much work done, novel research into new techniques and new areas of usage is far from over. This book presents some new theoretical as well as practical aspects of evolutionary computation. This book will be of great value to undergraduates, graduate students, researchers in computer science, and anyone else with an interest in learning about the latest developments in evolutionary computation.

Evolutionary Computation

This Third Edition provides the latest tools and techniques that enable computers to learn The Third Edition of this internationally acclaimed publication provides the latest theory and techniques for using simulated evolution to achieve ...

Evolutionary Computation

This Third Edition provides the latest tools and techniques thatenable computers to learn The Third Edition of this internationally acclaimed publicationprovides the latest theory and techniques for using simulatedevolution to achieve machine intelligence. As a leading advocatefor evolutionary computation, the author has successfullychallenged the traditional notion of artificial intelligence, whichessentially programs human knowledge fact by fact, but does nothave the capacity to learn or adapt as evolutionary computationdoes. Readers gain an understanding of the history of evolutionarycomputation, which provides a foundation for the author's thoroughpresentation of the latest theories shaping current research.Balancing theory with practice, the author provides readers withthe skills they need to apply evolutionary algorithms that cansolve many of today's intransigent problems by adapting to newchallenges and learning from experience. Several examples areprovided that demonstrate how these evolutionary algorithms learnto solve problems. In particular, the author provides a detailedexample of how an algorithm is used to evolve strategies forplaying chess and checkers. As readers progress through the publication, they gain anincreasing appreciation and understanding of the relationshipbetween learning and intelligence. Readers familiar with theprevious editions will discover much new and revised material thatbrings the publication thoroughly up to date with the latestresearch, including the latest theories and empirical properties ofevolutionary computation. The Third Edition also features new knowledge-building aids.Readers will find a host of new and revised examples. New questionsat the end of each chapter enable readers to test their knowledge.Intriguing assignments that prepare readers to manage challenges inindustry and research have been added to the end of each chapter aswell. This is a must-have reference for professionals in computer andelectrical engineering; it provides them with the very latesttechniques and applications in machine intelligence. With itsquestion sets and assignments, the publication is also recommendedas a graduate-level textbook.

Intelligence Computation and Evolutionary Computation

2012 International Conference of Intelligence Computation and Evolutionary Computation (ICEC 2012) is held on July 7, 2012 in Wuhan, China. This conference is sponsored by Information Technology & Industrial Engineering Research Center.

Intelligence Computation and Evolutionary Computation

2012 International Conference of Intelligence Computation and Evolutionary Computation (ICEC 2012) is held on July 7, 2012 in Wuhan, China. This conference is sponsored by Information Technology & Industrial Engineering Research Center. ICEC 2012 is a forum for presentation of new research results of intelligent computation and evolutionary computation. Cross-fertilization of intelligent computation, evolutionary computation, evolvable hardware and newly emerging technologies is strongly encouraged. The forum aims to bring together researchers, developers, and users from around the world in both industry and academia for sharing state-of-art results, for exploring new areas of research and development, and to discuss emerging issues facing intelligent computation and evolutionary computation.

The Routledge Research Companion to Electronic Music Reaching out with Technology

Moroni, A. and Manzolli, J. 2015. 'Robotics, Evolution and Interactivity in Sonic Art Installations'. In S. Washington (Ed.), New Developments in Evolutionary Computation Research. New York: Nova Science Publishers. pp.

The Routledge Research Companion to Electronic Music  Reaching out with Technology

The theme of this Research Companion is 'connectivity and the global reach of electroacoustic music and sonic arts made with technology'. The possible scope of such a companion in the field of electronic music has changed radically over the last 30 years. The definitions of the field itself are now broader - there is no clear boundary between 'electronic music' and 'sound art'. Also, what was previously an apparently simple divide between 'art' and 'popular' practices is now not easy or helpful to make, and there is a rich cluster of streams of practice with many histories, including world music traditions. This leads in turn to a steady undermining of a primarily Euro-American enterprise in the second half of the twentieth century. Telecommunications technology, most importantly the development of the internet in the final years of the century, has made materials, practices and experiences ubiquitous and apparently universally available - though some contributions to this volume reassert the influence and importance of local cultural practice. Research in this field is now increasingly multi-disciplinary. Technological developments are embedded in practices which may be musical, social, individual and collective. The contributors to this companion embrace technological, scientific, aesthetic, historical and social approaches and a host of hybrids – but, most importantly, they try to show how these join up. Thus the intention has been to allow a wide variety of new practices to have voice – unified through ideas of 'reaching out' and 'connecting together' – and in effect showing that there is emerging a different kind of 'global music'.

New Achievements in Evolutionary Computation

During this time, new metaheuristic optimization approaches, like evolutionary algorithms, genetic algorithms, ... researchers in computer science, and anyone else with an interest in learning about the latest developments in ...

New Achievements in Evolutionary Computation

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 of usage in artificial intelligence, machine learning, combinatorial and numerical optimization, etc., were being explored. However, even with so much work done, novel research into new techniques and new areas of usage is far from over. This book presents some new theoretical as well as practical aspects of evolutionary computation. This book will be of great value to undergraduates, graduate students, researchers in computer science, and anyone else with an interest in learning about the latest developments in evolutionary computation.

New Developments in Evolutionary Innovation

Research Policy , 11 ( 3 ) : 147–62 . Felin , T. , Kauffman , S. , Mastrogiorgio , A. , and ... Economics of Innovation and New Technology , 18 ( 4 ) : 311-36 . ... In Proceedings of the Genetic and Evolutionary Computation Conference .

New Developments in Evolutionary Innovation

Evolutionary thinking has had a profound impact on theories of technological innovation and strategy. This volume explores how significant advancements made in evolutionary biology since the 1970s influence evolutionary approaches to these areas, with an emphasis on the role of serendipity and unprestateability in innovation and novelty creation.

Recent Developments in Biologically Inspired Computing

He is known for his prolific research covering all aspects of evolutionary computation and digital biology. His research investigates evolutionary algorithms, ecological modeling, artificial immune systems, computational embryology and ...

Recent Developments in Biologically Inspired Computing

Recent Developments in Biologically Inspired Computing is necessary reading for undergraduate and graduate students, and researchers interested in knowing the most recent advances in problem solving techniques inspired by nature. This book covers the most relevant areas in computational intelligence, including evolutionary algorithms, artificial neural networks, artificial immune systems and swarm systems. It also brings together novel and philosophical trends in the exciting fields of artificial life and robotics. This book has the advantage of covering a large number of computational approaches, presenting the state-of-the-art before entering into the details of specific extensions and new developments. Pseudocodes, flow charts and examples of applications are provided so as to help newcomers and mature researchers to get the point of the new approaches presented.

Cost benefit Analysis and Evolutionary Computing

Salim , V.K. ( 2000 ) , Genetic Algorithms for the Evaluation and Scheduling of Urban Road Projects in Optimal ... Models and algorithms for road network design : a review and some new developments ' , Transport Reviews , 18 , 257-278 .

Cost benefit Analysis and Evolutionary Computing

"Demonstrating the application of evolutionary computing techniques to an exceptionally complex problem in the real business world, Cost-Benefit Analysis and Evolutionary Computing will be of great value to academics and those practitioners and researchers interested in addressing the classic issue of evaluating road expansion and maintenance programs."--BOOK JACKET.

Global Trends in Intelligent Computing Research and Development

Automatic clustering using an improved differential evolution algorithm. IEEE Transactions on Systems, ... New York: ACM. De Luca, A., & Termini, S. (1972). A definition of a nonprobabilistic entropy in the setting of fuzzy sets theory.

Global Trends in Intelligent Computing Research and Development

As the amount of accumulated data across a variety of fields becomes harder to maintain, it is essential for a new generation of computational theories and tools to assist humans in extracting knowledge from this rapidly growing digital data. Global Trends in Intelligent Computing Research and Development brings together recent advances and in depth knowledge in the fields of knowledge representation and computational intelligence. Highlighting the theoretical advances and their applications to real life problems, this book is an essential tool for researchers, lecturers, professors, students, and developers who have seek insight into knowledge representation and real life applications.

Evolutionary Algorithms for Solving Multi Objective Problems

"...If you still do not know this book, then, I urge you to run-don't walk-to your nearest on-line or off-line book purveyor and click, signal or otherwise buy this important addition to our literature.

Evolutionary Algorithms for Solving Multi Objective Problems

This textbook is a second edition of Evolutionary Algorithms for Solving Multi-Objective Problems, significantly expanded and adapted for the classroom. The various features of multi-objective evolutionary algorithms are presented here in an innovative and student-friendly fashion, incorporating state-of-the-art research. The book disseminates the application of evolutionary algorithm techniques to a variety of practical problems. It contains exhaustive appendices, index and bibliography and links to a complete set of teaching tutorials, exercises and solutions.

Recent Developments in Metaheuristics

Altogether, this book offers a comprehensive look at how researchers are currently using metaheuristics in different domains of design and application. This book highlights state-of-the-art developments in metaheuristics research.

Recent Developments in Metaheuristics

This book highlights state-of-the-art developments in metaheuristics research. It examines all aspects of metaheuristic research including new algorithmic developments, applications, new research challenges, theoretical developments, implementation issues, in-depth experimental studies. The book is divided into two sections. Part I is focused on new optimization and modeling techniques based on metaheuristics. The chapters in this section cover topics from multi-objective problems with fuzzy data with triangular-valued objective functions, to hyper-heuristics optimization methodology, designing genetic algorithms, and also the cuckoo search algorithm. The techniques described help to enhance the usability and increase the potential of metaheuristic algorithms. Part II showcases advanced metaheuristic approaches to solve real-life applications issues. This includes an examination of scheduling, the vehicle routing problem, multimedia sensor network, supplier selection, bin packing, objects tracking, and radio frequency identification. In the fields covered in the chapters are of high-impact applications of metaheuristics. The chapters offer innovative applications of metaheuristics that have a potential of widening research frontiers. Altogether, this book offers a comprehensive look at how researchers are currently using metaheuristics in different domains of design and application.

Swarm Intelligence and Evolutionary Algorithms in Healthcare and Drug Development

Every year numerous algorithms and techniques are proposed by researchers, and progressively more novel applications ... Swarm intelligence has emerged as a new-generation methodology belonging to the class of evolutionary computing.

Swarm Intelligence and Evolutionary Algorithms in Healthcare and Drug Development

Healthcare sector is characterized by difficulty, dynamism and variety. In 21st century, healthcare domain is surrounded by tons of challenges in terms of Disease detection, prevention, high costs, skilled technicians and better infrastructure. In order to handle these challenges, Intelligent Healthcare management technologies are required to play an effective role in improvising patient’s life. Healthcare organizations also need to continuously discover useful and actionable knowledge to gain insight from tons of data for various purposes for saving lives, reducing medical operations errors, enhancing efficiency, reducing costs and making the whole world a healthy world. Applying Swarm Intelligence and Evolutionary Algorithms in Healthcare and Drug Development is essential nowadays. The objective of this book is to highlight various Swarm Intelligence and Evolutionary Algorithms techniques for various medical issues in terms of Cancer Diagnosis, Brain Tumor, Diabetic Retinopathy, Heart disease as well as drug design and development. The book will act as one-stop reference for readers to think and explore Swarm Intelligence and Evolutionary Algorithms seriously for real-time patient diagnosis, as the book provides solutions to various complex diseases found critical for medical practitioners to diagnose in real-world. Key Features: Highlights the importance and applications of Swarm Intelligence and Evolutionary Algorithms in Healthcare industry. Elaborates Swarm Intelligence and Evolutionary Algorithms for Cancer Detection. In-depth coverage of computational methodologies, approaches and techniques based on Swarm Intelligence and Evolutionary Algorithms for detecting Brain Tumour including deep learning to optimize brain tumor diagnosis. Provides a strong foundation for Diabetic Retinopathy detection using Swarm and Evolutionary algorithms. Focuses on applying Swarm Intelligence and Evolutionary Algorithms for Heart Disease detection and diagnosis. Comprehensively covers the role of Swarm Intelligence and Evolutionary Algorithms for Drug Design and Discovery. The book will play a significant role for Researchers, Medical Practitioners, Healthcare Professionals and Industrial Healthcare Research and Development wings to conduct advanced research in Healthcare using Swarm Intelligence and Evolutionary Algorithms techniques.

Recent Advances in Evolutionary Computation for Combinatorial Optimization

This volume presents recent advances in the area of metaheuristic combinatorial optimisation, with a special focus on evolutionary computation methods. Moreover, it addresses local search methods and hybrid approaches.

Recent Advances in Evolutionary Computation for Combinatorial Optimization

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 pragmatic effectiveness. Such approaches are able to provide optimal or quasi-optimal solutions to a plethora of difficult combinatorial optimisation problems. The application of metaheuristics to combinatorial optimisation is an active field in which new theoretical developments, new algorithmic models, and new application areas are continuously emerging. This volume presents recent advances in the area of metaheuristic combinatorial optimisation, with a special focus on evolutionary computation methods. Moreover, it addresses local search methods and hybrid approaches. In this sense, the book includes cutting-edge theoretical, methodological, algorithmic and applied developments in the field, from respected experts and with a sound perspective.

Applications of Evolutionary Computing

... in marketing: New developments with implications for research and practice. Journal of Marketing 54 (1990) 3–19 4. Kohli, R., Krishnamurti, R.: Optimal product design using conjoint analysis: computational complexity and algorithms.

Applications of Evolutionary Computing

EvoWorkshops 2006, of which this volume contains the proceedings, was held in Budapest, Hungary, on April 10–12, 2006, jointly with EuroGP 2006 and EvoCOP 2006.

Evolutionary Computation in Gene Regulatory Network Research

This has led to a number of refinements of classic evolutionary theory in recent years. 10.3.1 Evolvability and Robustness Several related concepts from the 1950s have had a major impact on the evolutionary theory of development.

Evolutionary Computation in Gene Regulatory Network Research

Introducing a handbook for gene regulatory network research using evolutionary computation, with applications for computer scientists, computational and system biologists This book is a step-by-step guideline for research in gene regulatory networks (GRN) using evolutionary computation (EC). The book is organized into four parts that deliver materials in a way equally attractive for a reader with training in computation or biology. Each of these sections, authored by well-known researchers and experienced practitioners, provides the relevant materials for the interested readers. The first part of this book contains an introductory background to the field. The second part presents the EC approaches for analysis and reconstruction of GRN from gene expression data. The third part of this book covers the contemporary advancements in the automatic construction of gene regulatory and reaction networks and gives direction and guidelines for future research. Finally, the last part of this book focuses on applications of GRNs with EC in other fields, such as design, engineering and robotics. • Provides a reference for current and future research in gene regulatory networks (GRN) using evolutionary computation (EC) • Covers sub-domains of GRN research using EC, such as expression profile analysis, reverse engineering, GRN evolution, applications • Contains useful contents for courses in gene regulatory networks, systems biology, computational biology, and synthetic biology • Delivers state-of-the-art research in genetic algorithms, genetic programming, and swarm intelligence Evolutionary Computation in Gene Regulatory Network Research is a reference for researchers and professionals in computer science, systems biology, and bioinformatics, as well as upper undergraduate, graduate, and postgraduate students. Hitoshi Iba is a Professor in the Department of Information and Communication Engineering, Graduate School of Information Science and Technology, at the University of Tokyo, Toyko, Japan. He is an Associate Editor of the IEEE Transactions on Evolutionary Computation and the journal of Genetic Programming and Evolvable Machines. Nasimul Noman is a lecturer in the School of Electrical Engineering and Computer Science at the University of Newcastle, NSW, Australia. From 2002 to 2012 he was a faculty member at the University of Dhaka, Bangladesh. Noman is an Editor of the BioMed Research International journal. His research interests include computational biology, synthetic biology, and bioinformatics.

Fuzzy Evolutionary Computation

The main thrust of the book is to embark on a synergistic effect emerging between fuzzy sets and Evolutionary Computation ... We do hope that this volume will stimulate new developments in this fascinating research endeavor and foster ...

Fuzzy Evolutionary Computation

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 population -oriented methodology of structural and parametric optimization of a diversity of systems. In addition to this broad spectrum of such optimization applications, this paradigm otTers an important ability to cope with realistic goals and design objectives reflected in the form of relevant fitness functions. The GA search (which is often regarded as a dominant domain among other techniques of EC such as evolutionary strategies, genetic programming or evolutionary programming) delivers a great deal of efficiency helping navigate through large search spaces. The main thrust of fuzzy sets is in representing and managing nonnumeric (linguistic) information. The key notion (whose conceptual as weH as algorithmic importance has started to increase in the recent years) is that of information granularity. It somewhat concurs with the principle of incompatibility coined by L. A. Zadeh. Fuzzy sets form a vehic1e helpful in expressing a granular character of information to be captured. Once quantified via fuzzy sets or fuzzy relations, the domain knowledge could be used efficiently very often reducing a heavy computation burden when analyzing and optimizing complex systems.

Evolutionary Computation in Combinatorial Optimization

EvoCOP began in 2001 and has been held annually since then. It is the ?rst event speci?cally dedicated to the application of evolutionary computation and related methods to combinatorial optimization problems.

Evolutionary Computation in Combinatorial Optimization

Metaheuristics have been shown to be e?ective for di?cult combinatorial op- mization problems appearing in a wide variety of industrial, economic, and sci- ti?c domains. Prominent examples of metaheuristics are evolutionary algorithms, tabu search, simulated annealing, scatter search, memetic algorithms, variable neighborhood search, iterated local search, greedy randomized adaptive search procedures, ant colony optimization, and estimation of distribution algorithms. Problems solved successfully include scheduling, timetabling, network design, transportation and distribution, vehicle routing, the travelling salesman problem, packing and cutting, satis?ability, and general mixed integer programming. EvoCOP began in 2001 and has been held annually since then. It is the ?rst event speci?cally dedicated to the application of evolutionary computation and related methods to combinatorial optimization problems. Originally held as a workshop, EvoCOP became a conference in 2004. The events gave researchers an excellent opportunity to present their latest research and to discuss current - velopments and applications. Following the general trend of hybrid metaheur- tics and diminishing boundaries between the di?erent classes of metaheuristics, EvoCOP has broadened its scope in recent years and invited submissions on any kind of metaheuristic for combinatorial optimization.

Evolutionary Computation in Economics and Finance

The publications within “ Studies in Fuzziness and Soft Computing " are primarily monographs and edited volumes . They cover significant recent developments in the field , both of a foundational and applicational character .

Evolutionary Computation in Economics and Finance

After a decade's development, evolutionary computation (EC) proves to be a powerful tool kit for economic analysis. While the demand for this equipment is increasing, there is no volume exclusively written for economists. This volume for the first time helps economists to get a quick grasp on how EC may support their research. A comprehensive coverage of the subject is given, that includes the following three areas: game theory, agent-based economic modelling and financial engineering. Twenty leading scholars from each of these areas contribute a chapter to the volume. The reader will find himself treading the path of the history of this research area, from the fledgling stage to the burgeoning era. The results on games, labour markets, pollution control, institution and productivity, financial markets, trading systems design and derivative pricing, are new and interesting for different target groups. The book also includes informations on web sites, conferences, and computer software.