Memetic Computation

Download Memetic Computation full books in PDF, epub, and Kindle. Read online Memetic Computation ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

Memetic Computation

Author : Abhishek Gupta
Publisher : Springer
ISBN 13 : 3030027295
Total Pages : 104 pages
Book Rating : 4.0/5 (3 download)

DOWNLOAD NOW!

Book Synopsis Memetic Computation by : Abhishek Gupta

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

Evolutionary and Memetic Computing for Project Portfolio Selection and Scheduling

Author : Kyle Robert Harrison
Publisher : Springer Nature
ISBN 13 : 3030883159
Total Pages : 218 pages
Book Rating : 4.0/5 (38 download)

DOWNLOAD NOW!

Book Synopsis Evolutionary and Memetic Computing for Project Portfolio Selection and Scheduling by : Kyle Robert Harrison

Download or read book Evolutionary and Memetic Computing for Project Portfolio Selection and Scheduling written by Kyle Robert Harrison and published by Springer Nature. This book was released on 2021-11-13 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book consists of eight chapters, authored by distinguished researchers and practitioners, that highlight the state of the art and recent trends in addressing the project portfolio selection and scheduling problem (PPSSP) across a variety of domains, particularly defense, social programs, supply chains, and finance. Many organizations face the challenge of selecting and scheduling a subset of available projects subject to various resource and operational constraints. In the simplest scenario, the primary objective for an organization is to maximize the value added through funding and implementing a portfolio of projects, subject to the available budget. However, there are other major difficulties that are often associated with this problem such as qualitative project benefits, multiple conflicting objectives, complex project interdependencies, workforce and manufacturing constraints, and deep uncertainty regarding project costs, benefits, and completion times. It is well known that the PPSSP is an NP-hard problem and, thus, there is no known polynomial-time algorithm for this problem. Despite the complexity associated with solving the PPSSP, many traditional approaches to this problem make use of exact solvers. While exact solvers provide definitive optimal solutions, they quickly become prohibitively expensive in terms of computation time when the problem size is increased. In contrast, evolutionary and memetic computing afford the capability for autonomous heuristic approaches and expert knowledge to be combined and thereby provide an efficient means for high-quality approximation solutions to be attained. As such, these approaches can provide near real-time decision support information for portfolio design that can be used to augment and improve existing human-centric strategic decision-making processes. This edited book provides the reader with a broad overview of the PPSSP, its associated challenges, and approaches to addressing the problem using evolutionary and memetic computing.

Handbook of Memetic Algorithms

Author : Ferrante Neri
Publisher : Springer Science & Business Media
ISBN 13 : 3642232469
Total Pages : 376 pages
Book Rating : 4.6/5 (422 download)

DOWNLOAD NOW!

Book Synopsis Handbook of Memetic Algorithms by : Ferrante Neri

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

Swarm, Evolutionary, and Memetic Computing

Author : Bijaya Ketan Panigrahi
Publisher : Springer
ISBN 13 : 3642271723
Total Pages : 775 pages
Book Rating : 4.6/5 (422 download)

DOWNLOAD NOW!

Book Synopsis Swarm, Evolutionary, and Memetic Computing by : Bijaya Ketan Panigrahi

Download or read book Swarm, Evolutionary, and Memetic Computing written by Bijaya Ketan Panigrahi and published by Springer. This book was released on 2011-12-15 with total page 775 pages. Available in PDF, EPUB and Kindle. Book excerpt: These two volumes, LNCS 7076 and LNCS 7077, constitute the refereed proceedings of the Second International Conference on Swarm, Evolutionary, and Memetic Computing, SEMCCO 2011, held in Visakhapatnam, India, in December 2011. The 124 revised full papers presented in both volumes were carefully reviewed and selected from 422 submissions. The papers explore new application areas, feature new bio-inspired algorithms for solving specific hard optimization problems, and review the latest progresses in the cutting-edge research with swarm, evolutionary, and memetic computing in both theoretical and practical aspects.

Recent Advances in Memetic Algorithms

Author : William E. Hart
Publisher : Springer
ISBN 13 : 3540323635
Total Pages : 406 pages
Book Rating : 4.5/5 (43 download)

DOWNLOAD NOW!

Book Synopsis Recent Advances in Memetic Algorithms by : William E. Hart

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

Multi-Objective Memetic Algorithms

Author : Chi-Keong Goh
Publisher : Springer Science & Business Media
ISBN 13 : 354088050X
Total Pages : 399 pages
Book Rating : 4.5/5 (48 download)

DOWNLOAD NOW!

Book Synopsis Multi-Objective Memetic Algorithms by : Chi-Keong Goh

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

Computational Intelligence - Volume II

Author : Hisao Ishibuchi
Publisher : EOLSS Publications
ISBN 13 : 1780210213
Total Pages : 410 pages
Book Rating : 4.7/5 (82 download)

DOWNLOAD NOW!

Book Synopsis Computational Intelligence - Volume II by : Hisao Ishibuchi

Download or read book Computational Intelligence - Volume II written by Hisao Ishibuchi and published by EOLSS Publications. This book was released on 2015-12-30 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational intelligence is a component of Encyclopedia of Technology, Information, and Systems Management Resources in the global Encyclopedia of Life Support Systems (EOLSS), which is an integrated compendium of twenty one Encyclopedias. Computational intelligence is a rapidly growing research field including a wide variety of problem-solving techniques inspired by nature. Traditionally computational intelligence consists of three major research areas: Neural Networks, Fuzzy Systems, and Evolutionary Computation. Neural networks are mathematical models inspired by brains. Neural networks have massively parallel network structures with many neurons and weighted connections. Whereas each neuron has a simple input-output relation, a neural network with many neurons can realize a highly non-linear complicated mapping. Connection weights between neurons can be adjusted in an automated manner by a learning algorithm to realize a non-linear mapping required in a particular application task. Fuzzy systems are mathematical models proposed to handle inherent fuzziness in natural language. For example, it is very difficult to mathematically define the meaning of “cold” in everyday conversations such as “It is cold today” and “Can I have cold water”. The meaning of “cold” may be different in a different situation. Even in the same situation, a different person may have a different meaning. Fuzzy systems offer a mathematical mechanism to handle inherent fuzziness in natural language. As a result, fuzzy systems have been successfully applied to real-world problems by extracting linguistic knowledge from human experts in the form of fuzzy IF-THEN rules. Evolutionary computation includes various population-based search algorithms inspired by evolution in nature. Those algorithms usually have the following three mechanisms: fitness evaluation to measure the quality of each solution, selection to choose good solutions from the current population, and variation operators to generate offspring from parents. Evolutionary computation has high applicability to a wide range of optimization problems with different characteristics since it does not need any explicit mathematical formulations of objective functions. For example, simulation-based fitness evaluation is often used in evolutionary design. Subjective fitness evaluation by a human user is also often used in evolutionary art and music. These volumes are aimed at the following five major target audiences: University and College students Educators, Professional practitioners, Research personnel and Policy analysts, managers, and decision makers.

Bioinspired Computation in Artificial Systems

Author : José Manuel Ferrández Vicente
Publisher : Springer
ISBN 13 : 331918833X
Total Pages : 485 pages
Book Rating : 4.3/5 (191 download)

DOWNLOAD NOW!

Book Synopsis Bioinspired Computation in Artificial Systems by : José Manuel Ferrández Vicente

Download or read book Bioinspired Computation in Artificial Systems written by José Manuel Ferrández Vicente and published by Springer. This book was released on 2015-05-22 with total page 485 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two volumes LNCS 9107 and 9108 constitute the proceedings of the International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2015, held in Elche, Spain, in June 2015. The total of 103 contributions was carefully reviewed and selected from 190 submissions during two rounds of reviewing and improvement. The papers are organized in two volumes, one on artificial computation and biology and medicine, addressing topics such as computational neuroscience, neural coding and neuro-informatics, as well as computational foundations and approaches to the study of cognition. The second volume deals with bioinspired computation in artificial systems; topics alluded are bio-inspired circuits and mechanisms, bioinspired programming strategies, and bioinspired engineering AI&KE.

Business and Consumer Analytics: New Ideas

Author : Pablo Moscato
Publisher : Springer
ISBN 13 : 3030062228
Total Pages : 1005 pages
Book Rating : 4.0/5 (3 download)

DOWNLOAD NOW!

Book Synopsis Business and Consumer Analytics: New Ideas by : Pablo Moscato

Download or read book Business and Consumer Analytics: New Ideas written by Pablo Moscato and published by Springer. This book was released on 2019-05-30 with total page 1005 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume handbook presents a collection of novel methodologies with applications and illustrative examples in the areas of data-driven computational social sciences. Throughout this handbook, the focus is kept specifically on business and consumer-oriented applications with interesting sections ranging from clustering and network analysis, meta-analytics, memetic algorithms, machine learning, recommender systems methodologies, parallel pattern mining and data mining to specific applications in market segmentation, travel, fashion or entertainment analytics. A must-read for anyone in data-analytics, marketing, behavior modelling and computational social science, interested in the latest applications of new computer science methodologies. The chapters are contributed by leading experts in the associated fields.The chapters cover technical aspects at different levels, some of which are introductory and could be used for teaching. Some chapters aim at building a common understanding of the methodologies and recent application areas including the introduction of new theoretical results in the complexity of core problems. Business and marketing professionals may use the book to familiarize themselves with some important foundations of data science. The work is a good starting point to establish an open dialogue of communication between professionals and researchers from different fields. Together, the two volumes present a number of different new directions in Business and Customer Analytics with an emphasis in personalization of services, the development of new mathematical models and new algorithms, heuristics and metaheuristics applied to the challenging problems in the field. Sections of the book have introductory material to more specific and advanced themes in some of the chapters, allowing the volumes to be used as an advanced textbook. Clustering, Proximity Graphs, Pattern Mining, Frequent Itemset Mining, Feature Engineering, Network and Community Detection, Network-based Recommending Systems and Visualization, are some of the topics in the first volume. Techniques on Memetic Algorithms and their applications to Business Analytics and Data Science are surveyed in the second volume; applications in Team Orienteering, Competitive Facility-location, and Visualization of Products and Consumers are also discussed. The second volume also includes an introduction to Meta-Analytics, and to the application areas of Fashion and Travel Analytics. Overall, the two-volume set helps to describe some fundamentals, acts as a bridge between different disciplines, and presents important results in a rapidly moving field combining powerful optimization techniques allied to new mathematical models critical for personalization of services. Academics and professionals working in the area of business anyalytics, data science, operations research and marketing will find this handbook valuable as a reference. Students studying these fields will find this handbook useful and helpful as a secondary textbook.

Introduction to Evolutionary Computing

Author : A.E. Eiben
Publisher : Springer
ISBN 13 : 3662448742
Total Pages : 294 pages
Book Rating : 4.6/5 (624 download)

DOWNLOAD NOW!

Book Synopsis Introduction to Evolutionary Computing by : A.E. Eiben

Download or read book Introduction to Evolutionary Computing written by A.E. Eiben and published by Springer. This book was released on 2015-07-01 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: The overall structure of this new edition is three-tier: Part I presents the basics, Part II is concerned with methodological issues, and Part III discusses advanced topics. In the second edition the authors have reorganized the material to focus on problems, how to represent them, and then how to choose and design algorithms for different representations. They also added a chapter on problems, reflecting the overall book focus on problem-solvers, a chapter on parameter tuning, which they combined with the parameter control and "how-to" chapters into a methodological part, and finally a chapter on evolutionary robotics with an outlook on possible exciting developments in this field. The book is suitable for undergraduate and graduate courses in artificial intelligence and computational intelligence, and for self-study by practitioners and researchers engaged with all aspects of bioinspired design and optimization.

Evolutionary and Swarm Intelligence Algorithms

Author : Jagdish Chand Bansal
Publisher : Springer
ISBN 13 : 3319913417
Total Pages : 194 pages
Book Rating : 4.3/5 (199 download)

DOWNLOAD NOW!

Book Synopsis Evolutionary and Swarm Intelligence Algorithms by : Jagdish Chand Bansal

Download or read book Evolutionary and Swarm Intelligence Algorithms written by Jagdish Chand Bansal and published by Springer. This book was released on 2018-06-06 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 evolutionary algorithms with a focus on their applications in engineering problems in diverse domains. The topics discussed include particle swarm optimization, the artificial bee colony algorithm, Spider Monkey optimization algorithm, genetic algorithms, constrained multi-objective evolutionary algorithms, genetic programming, and evolutionary fuzzy systems. A friendly and informative treatment of the topics makes this book an ideal reference for beginners and those with experience alike.

Optinformatics in Evolutionary Learning and Optimization

Author : Liang Feng
Publisher : Springer Nature
ISBN 13 : 3030709205
Total Pages : 144 pages
Book Rating : 4.0/5 (37 download)

DOWNLOAD NOW!

Book Synopsis Optinformatics in Evolutionary Learning and Optimization by : Liang Feng

Download or read book Optinformatics in Evolutionary Learning and Optimization written by Liang Feng and published by Springer Nature. This book was released on 2021-03-29 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides readers the recent algorithmic advances towards realizing the notion of optinformatics in evolutionary learning and optimization. The book also provides readers a variety of practical applications, including inter-domain learning in vehicle route planning, data-driven techniques for feature engineering in automated machine learning, as well as evolutionary transfer reinforcement learning. Through reading this book, the readers will understand the concept of optinformatics, recent research progresses in this direction, as well as particular algorithm designs and application of optinformatics. Evolutionary algorithms (EAs) are adaptive search approaches that take inspiration from the principles of natural selection and genetics. Due to their efficacy of global search and ease of usage, EAs have been widely deployed to address complex optimization problems occurring in a plethora of real-world domains, including image processing, automation of machine learning, neural architecture search, urban logistics planning, etc. Despite the success enjoyed by EAs, it is worth noting that most existing EA optimizers conduct the evolutionary search process from scratch, ignoring the data that may have been accumulated from different problems solved in the past. However, today, it is well established that real-world problems seldom exist in isolation, such that harnessing the available data from related problems could yield useful information for more efficient problem-solving. Therefore, in recent years, there is an increasing research trend in conducting knowledge learning and data processing along the course of an optimization process, with the goal of achieving accelerated search in conjunction with better solution quality. To this end, the term optinformatics has been coined in the literature as the incorporation of information processing and data mining (i.e., informatics) techniques into the optimization process. The primary market of this book is researchers from both academia and industry, who are working on computational intelligence methods and their applications. This book is also written to be used as a textbook for a postgraduate course in computational intelligence emphasizing methodologies at the intersection of optimization and machine learning.

Applications of Evolutionary Computation

Author : Antonio M. Mora
Publisher : Springer
ISBN 13 : 3319165496
Total Pages : 914 pages
Book Rating : 4.3/5 (191 download)

DOWNLOAD NOW!

Book Synopsis Applications of Evolutionary Computation by : Antonio M. Mora

Download or read book Applications of Evolutionary Computation written by Antonio M. Mora and published by Springer. This book was released on 2015-03-16 with total page 914 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed conference proceedings of the 18th International Conference on the Applications of Evolutionary Computation, EvoApplications 2015, held in Copenhagen, Spain, in April 2015, colocated with the Evo 2015 events EuroGP, EvoCOP, and EvoMUSART. The 72 revised full papers presented were carefully reviewed and selected from 125 submissions. EvoApplications 2015 consisted of the following 13 tracks: EvoBIO (evolutionary computation, machine learning and data mining in computational biology), EvoCOMNET (nature-inspired techniques for telecommunication networks and other parallel and distributed systems), EvoCOMPLEX (evolutionary algorithms and complex systems), EvoENERGY (evolutionary computation in energy applications), EvoFIN (evolutionary and natural computation in finance and economics), EvoGAMES (bio-inspired algorithms in games), EvoIASP (evolutionary computation in image analysis, signal processing, and pattern recognition), EvoINDUSTRY (nature-inspired techniques in industrial settings), EvoNUM (bio-inspired algorithms for continuous parameter optimization), EvoPAR (parallel implementation of evolutionary algorithms), EvoRISK (computational intelligence for risk management, security and defence applications), EvoROBOT (evolutionary computation in robotics), and EvoSTOC (evolutionary algorithms in stochastic and dynamic environments).

Simulated Evolution and Learning

Author : Lam Thu Bui
Publisher : Springer
ISBN 13 : 3642348599
Total Pages : 525 pages
Book Rating : 4.6/5 (423 download)

DOWNLOAD NOW!

Book Synopsis Simulated Evolution and Learning by : Lam Thu Bui

Download or read book Simulated Evolution and Learning written by Lam Thu Bui and published by Springer. This book was released on 2012-12-02 with total page 525 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes the proceedings of the 9th International Conference on Simulated Evolution and Learning, SEAL 2012, held in Hanoi, Vietnam, in December 2012. The 50 full papers presented were carefully reviewed and selected from 91 submissions. The papers are organized in topical sections on evolutionary algorithms, theoretical developments, swarm intelligence, data mining, learning methodologies, and real-world applications.

Soft Computing for Problem Solving 2019

Author : Atulya K. Nagar
Publisher : Springer Nature
ISBN 13 : 9811532877
Total Pages : 223 pages
Book Rating : 4.8/5 (115 download)

DOWNLOAD NOW!

Book Synopsis Soft Computing for Problem Solving 2019 by : Atulya K. Nagar

Download or read book Soft Computing for Problem Solving 2019 written by Atulya K. Nagar and published by Springer Nature. This book was released on 2020-04-04 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book features the outcomes of the 9th International Conference on Soft Computing for Problem Solving, SocProS 2019, which brought together researchers, engineers and practitioners to discuss thought-provoking developments and challenges in order to identify potential future directions. The book presents the latest advances and innovations in the interdisciplinary areas of soft computing, including original research papers in areas such as algorithms (artificial immune systems, artificial neural networks, genetic algorithms, genetic programming, and particle swarm optimization) and applications (control systems, data mining and clustering, finance, weather forecasting, game theory, business and forecasting applications). It is a valuable resource for both young and experienced researchers dealing with complex and intricate real-world problems that cannot easily be solved using traditional methods.

Natural Computing Algorithms

Author : Anthony Brabazon
Publisher : Springer
ISBN 13 : 3662436310
Total Pages : 554 pages
Book Rating : 4.6/5 (624 download)

DOWNLOAD NOW!

Book Synopsis Natural Computing Algorithms by : Anthony Brabazon

Download or read book Natural Computing Algorithms written by Anthony Brabazon and published by Springer. This book was released on 2015-10-08 with total page 554 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of natural computing has been the focus of a substantial research effort in recent decades. One particular strand of this research concerns the development of computational algorithms using metaphorical inspiration from systems and phenomena that occur in the natural world. These naturally inspired computing algorithms have proven to be successful problem-solvers across domains as diverse as management science, bioinformatics, finance, marketing, engineering, architecture and design. This book is a comprehensive introduction to natural computing algorithms, suitable for academic and industrial researchers and for undergraduate and graduate courses on natural computing in computer science, engineering and management science.

Applications of Evolutionary Computation

Author : Giovanni Squillero
Publisher : Springer
ISBN 13 : 3319558498
Total Pages : 912 pages
Book Rating : 4.3/5 (195 download)

DOWNLOAD NOW!

Book Synopsis Applications of Evolutionary Computation by : Giovanni Squillero

Download or read book Applications of Evolutionary Computation written by Giovanni Squillero and published by Springer. This book was released on 2017-04-03 with total page 912 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two volumes LNCS 10199 and 10200 constitute the refereed conference proceedings of the 20th European Conference on the Applications of Evolutionary Computation, EvoApplications 2017, held in Amsterdam, The Netherlands, in April 2017, collocated with the Evo* 2016 events EuroGP, EvoCOP, and EvoMUSART. The 46 revised full papers presented together with 26 poster papers were carefully reviewed and selected from 108 submissions. EvoApplications 2016 consisted of the following 13 tracks: EvoBAFIN (natural computing methods in business analytics and finance), EvoBIO (evolutionary computation, machine learning and data mining in computational biology), EvoCOMNET (nature-inspired techniques for telecommunication networks and other parallel and distributed systems), EvoCOMPLEX (evolutionary algorithms and complex systems), EvoENERGY (evolutionary computation in energy applications), EvoGAMES (bio-inspired algorithms in games), EvoIASP (evolutionary computation in image analysis, signal processing, and pattern recognition), EvoINDUSTRY (nature-inspired techniques in industrial settings), EvoKNOW (knowledge incorporation in evolutionary computation), EvoNUM (bio-inspired algorithms for continuous parameter optimization), EvoPAR (parallel implementation of evolutionary algorithms), EvoROBOT (evolutionary robotics), EvoSET (nature-inspired algorithms in software engineering and testing), and EvoSTOC (evolutionary algorithms in stochastic and dynamic environments).