Memetic Computation

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Memetic Computation

Abhishek Gupta,Yew-Soon Ong
Memetic Computation Book PDF

Author : Abhishek Gupta,Yew-Soon Ong
Publisher : Springer
Page : 104 pages
File Size : 51,6 Mb
Release : 2018-12-18
Category : Technology & Engineering
ISBN : 9783030027292

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Memetic Computation by Abhishek Gupta,Yew-Soon Ong Pdf

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

Kyle Robert Harrison,Saber Elsayed,Ivan Leonidovich Garanovich,Terence Weir,Sharon G. Boswell,Ruhul Amin Sarker
Evolutionary and Memetic Computing for Project Portfolio Selection and Scheduling Book PDF

Author : Kyle Robert Harrison,Saber Elsayed,Ivan Leonidovich Garanovich,Terence Weir,Sharon G. Boswell,Ruhul Amin Sarker
Publisher : Springer Nature
Page : 218 pages
File Size : 55,6 Mb
Release : 2021-11-13
Category : Technology & Engineering
ISBN : 9783030883157

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Evolutionary and Memetic Computing for Project Portfolio Selection and Scheduling by Kyle Robert Harrison,Saber Elsayed,Ivan Leonidovich Garanovich,Terence Weir,Sharon G. Boswell,Ruhul Amin Sarker Pdf

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.

Swarm, Evolutionary, and Memetic Computing

Bijaya Ketan Panigrahi,Swagatam Das,Ponnuthurai Nagaratnam Suganthan,Subhransu Sekhar Dash
Swarm Evolutionary and Memetic Computing Book PDF

Author : Bijaya Ketan Panigrahi,Swagatam Das,Ponnuthurai Nagaratnam Suganthan,Subhransu Sekhar Dash
Publisher : Springer
Page : 772 pages
File Size : 43,9 Mb
Release : 2010-12-06
Category : Computers
ISBN : 9783642175633

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Swarm, Evolutionary, and Memetic Computing by Bijaya Ketan Panigrahi,Swagatam Das,Ponnuthurai Nagaratnam Suganthan,Subhransu Sekhar Dash Pdf

This LNCS volume contains the papers presented at the First Swarm, Evolutionary and Memetic Computing Conference (SEMCCO 2010) held during December 16–– 18, 2010 at SRM University, Chennai, in India. SEMCCO 2010 marked the beginning of a prestigious international conference series that aims at bringing together researchers from academia and industry to report and review the latest progress in the cutting-edge research on swarm, evolutionary, and memetic computing, to explore new application areas, to design new bio-inspired algorithms for solving specific hard optimization problems, and finally to create awareness on these domains to a wider audience of practitioners. SEMCCO 2010 received 225 paper submissions from 20 countries across the globe. After a rigorous peer-review process involving 610 reviews in total, 90 fu- length articles were accepted for oral presentation at the conference. This corresponds to an acceptance rate of 40% and is intended for maintaining the high standards of the conference proceedings. The papers included in this LNCS volume cover a wide range of topics in swarm, evolutionary, and memetic computing algorithms and their real-world applications in problems selected from diverse domains of science and engineering.

Handbook of Memetic Algorithms

Ferrante Neri,Carlos Cotta,Pablo Moscato
Handbook of Memetic Algorithms Book PDF

Author : Ferrante Neri,Carlos Cotta,Pablo Moscato
Publisher : Springer Science & Business Media
Page : 376 pages
File Size : 42,8 Mb
Release : 2011-10-18
Category : Mathematics
ISBN : 9783642232466

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Handbook of Memetic Algorithms by Ferrante Neri,Carlos Cotta,Pablo Moscato Pdf

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.

Computational Intelligence - Volume II

Hisao Ishibuchi
Computational Intelligence Volume II Book PDF

Author : Hisao Ishibuchi
Publisher : EOLSS Publications
Page : 410 pages
File Size : 49,9 Mb
Release : 2015-12-30
Category : Electronic
ISBN : 9781780210216

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Computational Intelligence - Volume II by Hisao Ishibuchi Pdf

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.

Soft Computing for Problem Solving 2019

Atulya K. Nagar,Kusum Deep,Jagdish Chand Bansal,Kedar Nath Das
Soft Computing for Problem Solving 2019 Book PDF

Author : Atulya K. Nagar,Kusum Deep,Jagdish Chand Bansal,Kedar Nath Das
Publisher : Springer Nature
Page : 223 pages
File Size : 55,5 Mb
Release : 2020-04-04
Category : Technology & Engineering
ISBN : 9789811532870

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Soft Computing for Problem Solving 2019 by Atulya K. Nagar,Kusum Deep,Jagdish Chand Bansal,Kedar Nath Das Pdf

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.

Recent Advances in Memetic Algorithms

William E. Hart,Natalio Krasnogor,J.E. Smith
Recent Advances in Memetic Algorithms Book PDF

Author : William E. Hart,Natalio Krasnogor,J.E. Smith
Publisher : Springer
Page : 406 pages
File Size : 46,8 Mb
Release : 2006-06-22
Category : Mathematics
ISBN : 9783540323631

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Recent Advances in Memetic Algorithms by William E. Hart,Natalio Krasnogor,J.E. Smith Pdf

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.

Optinformatics in Evolutionary Learning and Optimization

Liang Feng,Yaqing Hou,Zexuan Zhu
Optinformatics in Evolutionary Learning and Optimization Book PDF

Author : Liang Feng,Yaqing Hou,Zexuan Zhu
Publisher : Springer Nature
Page : 144 pages
File Size : 49,5 Mb
Release : 2021-03-29
Category : Technology & Engineering
ISBN : 9783030709204

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Optinformatics in Evolutionary Learning and Optimization by Liang Feng,Yaqing Hou,Zexuan Zhu Pdf

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.

Artificial Life and Computational Intelligence

Tapabrata Ray,Ruhul Sarker,Xiaodong Li
Artificial Life and Computational Intelligence Book PDF

Author : Tapabrata Ray,Ruhul Sarker,Xiaodong Li
Publisher : Springer
Page : 375 pages
File Size : 40,8 Mb
Release : 2016-01-22
Category : Computers
ISBN : 9783319282701

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Artificial Life and Computational Intelligence by Tapabrata Ray,Ruhul Sarker,Xiaodong Li Pdf

This book constitutes the proceedings of the Second Australasian Conference on Artificial Life and Computational Intelligence, ACALCI 2016, held in Canberra, ACT, Australia, in February 2016. The 30 full papers presented in this volume were carefully reviewed and selected from 41 submissions. They are organized in topical sections named: mathematical modeling and theory; learning and optimization; planning and scheduling; feature selection; and applications and games.

Search and Optimization by Metaheuristics

Ke-Lin Du,M. N. S. Swamy
Search and Optimization by Metaheuristics Book PDF

Author : Ke-Lin Du,M. N. S. Swamy
Publisher : Birkhäuser
Page : 434 pages
File Size : 41,6 Mb
Release : 2016-07-20
Category : Computers
ISBN : 9783319411927

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Search and Optimization by Metaheuristics by Ke-Lin Du,M. N. S. Swamy Pdf

This textbook provides a comprehensive introduction to nature-inspired metaheuristic methods for search and optimization, including the latest trends in evolutionary algorithms and other forms of natural computing. Over 100 different types of these methods are discussed in detail. The authors emphasize non-standard optimization problems and utilize a natural approach to the topic, moving from basic notions to more complex ones. An introductory chapter covers the necessary biological and mathematical backgrounds for understanding the main material. Subsequent chapters then explore almost all of the major metaheuristics for search and optimization created based on natural phenomena, including simulated annealing, recurrent neural networks, genetic algorithms and genetic programming, differential evolution, memetic algorithms, particle swarm optimization, artificial immune systems, ant colony optimization, tabu search and scatter search, bee and bacteria foraging algorithms, harmony search, biomolecular computing, quantum computing, and many others. General topics on dynamic, multimodal, constrained, and multiobjective optimizations are also described. Each chapter includes detailed flowcharts that illustrate specific algorithms and exercises that reinforce important topics. Introduced in the appendix are some benchmarks for the evaluation of metaheuristics. Search and Optimization by Metaheuristics is intended primarily as a textbook for graduate and advanced undergraduate students specializing in engineering and computer science. It will also serve as a valuable resource for scientists and researchers working in these areas, as well as those who are interested in search and optimization methods.

Swarm, Evolutionary, and Memetic Computing

Bijaya Ketan Panigrahi,Ponnuthurai Nagaratnam Suganthan,Swagatam Das,Suresh Chandra Satapathy
Swarm Evolutionary and Memetic Computing Book PDF

Author : Bijaya Ketan Panigrahi,Ponnuthurai Nagaratnam Suganthan,Swagatam Das,Suresh Chandra Satapathy
Publisher : Springer
Page : 754 pages
File Size : 54,8 Mb
Release : 2011-12-15
Category : Computers
ISBN : 9783642271724

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Swarm, Evolutionary, and Memetic Computing by Bijaya Ketan Panigrahi,Ponnuthurai Nagaratnam Suganthan,Swagatam Das,Suresh Chandra Satapathy Pdf

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.

Data-Driven Scheduling of Semiconductor Manufacturing Systems

Li Li,Qingyun Yu,Kuo-Yi Lin,Yumin Ma,Fei Qiao
Data Driven Scheduling of Semiconductor Manufacturing Systems Book PDF

Author : Li Li,Qingyun Yu,Kuo-Yi Lin,Yumin Ma,Fei Qiao
Publisher : Springer Nature
Page : 276 pages
File Size : 51,7 Mb
Release : 2023-05-20
Category : Technology & Engineering
ISBN : 9789811975882

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Data-Driven Scheduling of Semiconductor Manufacturing Systems by Li Li,Qingyun Yu,Kuo-Yi Lin,Yumin Ma,Fei Qiao Pdf

This book systematically discusses the intelligent scheduling problem of complex semiconductor manufacturing systems from theory to method and then to application. The main contents include data-driven scheduling framework of semiconductor manufacturing system, data preprocessing of semiconductor manufacturing system, correlation analysis of performance index of semiconductor production line, intelligent release control strategy, dynamic dispatching rules simulating pheromone mechanism, and load balancing dynamic scheduling of semiconductor production line, performance index-driven dynamic scheduling method of semiconductor production line, scheduling trend of semi-conductor manufacturing system in big data environment. This book aims to provide readers with valuable reference and assistance in the theoretical methods, techniques, and application cases of semiconductor manufacturing systems and their intelligent scheduling.

Bioinspired Computation in Artificial Systems

José Manuel Ferrández Vicente,José Ramón Álvarez-Sánchez,Félix de la Paz López,Fco. Javier Toledo-Moreo,Hojjat Adeli
Bioinspired Computation in Artificial Systems Book PDF

Author : José Manuel Ferrández Vicente,José Ramón Álvarez-Sánchez,Félix de la Paz López,Fco. Javier Toledo-Moreo,Hojjat Adeli
Publisher : Springer
Page : 462 pages
File Size : 49,8 Mb
Release : 2015-05-22
Category : Computers
ISBN : 9783319188331

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Bioinspired Computation in Artificial Systems by José Manuel Ferrández Vicente,José Ramón Álvarez-Sánchez,Félix de la Paz López,Fco. Javier Toledo-Moreo,Hojjat Adeli Pdf

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.

Natural Computing Algorithms

Anthony Brabazon,Michael O'Neill,Seán McGarraghy
Natural Computing Algorithms Book PDF

Author : Anthony Brabazon,Michael O'Neill,Seán McGarraghy
Publisher : Springer
Page : 554 pages
File Size : 44,6 Mb
Release : 2015-10-08
Category : Computers
ISBN : 9783662436318

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Natural Computing Algorithms by Anthony Brabazon,Michael O'Neill,Seán McGarraghy Pdf

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.

Introduction to Evolutionary Computing

A.E. Eiben,J.E. Smith
Introduction to Evolutionary Computing Book PDF

Author : A.E. Eiben,J.E. Smith
Publisher : Springer
Page : 287 pages
File Size : 53,5 Mb
Release : 2015-07-01
Category : Computers
ISBN : 9783662448748

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Introduction to Evolutionary Computing by A.E. Eiben,J.E. Smith Pdf

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.