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| evolutionary multiobjective optimization theoretical advances and applications: Evolutionary Multiobjective Optimization Ajith Abraham, L. C. Jain, 2005-04-22 Evolutionary Multiobjective Optimization is a rare collection of the latest state-of-the-art theoretical research, design challenges and applications in the field of multiobjective optimization paradigms using evolutionary algorithms. It includes two introductory chapters giving all the fundamental definitions, several complex test functions and a practical problem involving the multiobjective optimization of space structures under static and seismic loading conditions used to illustrate the various multiobjective optimization concepts. Important features include: Detailed overview of all the multiobjective optimization paradigms using evolutionary algorithms Excellent coverage of timely, advanced multiobjective optimization topics State-of-the-art theoretical research and application developments Chapters authored by pioneers in the field Academics and industrial scientists as well as engineers engaged in research, development and application of evolutionary algorithm based Multiobjective Optimization will find the comprehensive coverage of this book invaluable. |
| evolutionary multiobjective optimization theoretical advances and applications: Multi-objective Swarm Intelligence Satchidananda Dehuri, Alok Kumar Jagadev, Mrutyunjaya Panda, 2015-03-10 The aim of this book is to understand the state-of-the-art theoretical and practical advances of swarm intelligence. It comprises seven contemporary relevant chapters. In chapter 1, a review of Bacteria Foraging Optimization (BFO) techniques for both single and multiple criterions problem is presented. A survey on swarm intelligence for multiple and many objectives optimization is presented in chapter 2 along with a topical study on EEG signal analysis. Without compromising the extensive simulation study, a comparative study of variants of MOPSO is provided in chapter 3. Intractable problems like subset and job scheduling problems are discussed in chapters 4 and 7 by different hybrid swarm intelligence techniques. An attempt to study image enhancement by ant colony optimization is made in chapter 5. Finally, chapter 7 covers the aspect of uncertainty in data by hybrid PSO. |
| evolutionary multiobjective optimization theoretical advances and applications: Applications of Multi-objective Evolutionary Algorithms Carlos A. Coello Coello, Gary B. Lamont, 2004 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 high-dimensional real-world design applications. The book contains a large collection of MOEA applications from many researchers, and thus provides the practitioner with detailed algorithmic direction to achieve good results in their selected problem domain. |
| evolutionary multiobjective optimization theoretical advances and applications: Evolutionary Multi-Criterion Optimization Matthias Ehrgott, Carlos M. Fonseca, Xavier Gandibleux, Jin-Kao Hao, Marc Sevaux, 2009-03-26 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 and selected from 72 submissions. The papers are organized in topical sections on theoretical analysis, uncertainty and noise, algorithm development, performance analysis and comparison, applications, MCDM Track, Many objectives, alternative methods, as well as EMO and MCDA. |
| evolutionary multiobjective optimization theoretical advances and applications: Evolutionary Multiobjective Optimization Ajith Abraham, Robert Goldberg, 2005-09-05 Evolutionary Multi-Objective Optimization is an expanding field of research. This book brings a collection of papers with some of the most recent advances in this field. The topic and content is currently very fashionable and has immense potential for practical applications and includes contributions from leading researchers in the field. Assembled in a compelling and well-organised fashion, Evolutionary Computation Based Multi-Criteria Optimization will prove beneficial for both academic and industrial scientists and engineers engaged in research and development and application of evolutionary algorithm based MCO. Packed with must-find information, this book is the first to comprehensively and clearly address the issue of evolutionary computation based MCO, and is an essential read for any researcher or practitioner of the technique. |
| evolutionary multiobjective optimization theoretical advances and applications: Advances in Differential Evolution Uday K. Chakraborty, 2008-07-23 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 focus on algorithm design, while the last seven describe real-world applications. Chapter 1 introduces the basic differential evolution (DE) algorithm and presents a broad overview of the field. Chapter 2 presents a new, rotationally invariant DE algorithm. The role of self-adaptive control parameters in DE is investigated in Chapter 3. Chapters 4 and 5 address constrained optimization; the former develops suitable stopping conditions for the DE run, and the latter presents an improved DE algorithm for problems with very small feasible regions. A novel DE algorithm, based on the concept of opposite points, is the topic of Chapter 6. Chapter 7 provides a survey of multi-objective differential evolution algorithms. A review of the major application areas of differential evolution is presented in Chapter 8. Chapter 9 discusses the application of differential evolution in two important areas of applied electromagnetics. Chapters 10 and 11 focus on applications of hybrid DE algorithms to problems in power system optimization. Chapter 12 applies the DE algorithm to computer chess. The use of DE to solve a problem in bioprocess engineering is discussed in Chapter 13. Chapter 14 describes the application of hybrid differential evolution to a problem in control engineering. |
| evolutionary multiobjective optimization theoretical advances and applications: Evolutionary Algorithms for Solving Multi-Objective Problems Carlos Coello Coello, Gary B. Lamont, David A. van Veldhuizen, 2007-09-18 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. |
| evolutionary multiobjective optimization theoretical advances and applications: Theoretical Advances and Applications of Fuzzy Logic and Soft Computing Oscar Castillo, Patricia Melin, Oscar Montiel Ross, Witold Pedrycz, Roberto Sepúlveda Cruz, 2007-06-08 This book comprises a selection of papers on theoretical advances and applications of fuzzy logic and soft computing from the IFSA 2007 World Congress, held in Cancun, Mexico, June 2007. These papers constitute an important contribution to the theory and applications of fuzzy logic and soft computing methodologies. |
| evolutionary multiobjective optimization theoretical advances and applications: Theory of Randomized Search Heuristics Anne Auger, Benjamin Doerr, 2011 This volume covers both classical results and the most recent theoretical developments in the field of randomized search heuristics such as runtime analysis, drift analysis and convergence. |
| evolutionary multiobjective optimization theoretical advances and applications: Parallel Problem Solving from Nature - PPSN IX Thomas Philip Runarsson, Hans-Georg Beyer, Edmund Burke, Juan J. Merelo-Guervós, L. Darrell Whitley, Xin Yao, 2006-10-06 This book constitutes the refereed proceedings of the 9th International Conference on Parallel Problem Solving from Nature, PPSN 2006. The book presents 106 revised full papers covering a wide range of topics, from evolutionary computation to swarm intelligence and bio-inspired computing to real-world applications. These are organized in topical sections on theory, new algorithms, applications, multi-objective optimization, evolutionary learning, as well as representations, operators, and empirical evaluation. |
| evolutionary multiobjective optimization theoretical advances and applications: Multi-Objective Optimization using Evolutionary Algorithms Kalyanmoy Deb, 2001-07-05 Evolutionary algorithms are relatively new, but very powerful techniques used to find solutions to many real-world search and optimization problems. Many of these problems have multiple objectives, which leads to the need to obtain a set of optimal solutions, known as effective solutions. It has been found that using evolutionary algorithms is a highly effective way of finding multiple effective solutions in a single simulation run. Comprehensive coverage of this growing area of research Carefully introduces each algorithm with examples and in-depth discussion Includes many applications to real-world problems, including engineering design and scheduling Includes discussion of advanced topics and future research Can be used as a course text or for self-study Accessible to those with limited knowledge of classical multi-objective optimization and evolutionary algorithms The integrated presentation of theory, algorithms and examples will benefit those working and researching in the areas of optimization, optimal design and evolutionary computing. This text provides an excellent introduction to the use of evolutionary algorithms in multi-objective optimization, allowing use as a graduate course text or for self-study. |
| evolutionary multiobjective optimization theoretical advances and applications: Multiobjective Optimization Jürgen Branke, 2008-10-15 Multiobjective optimization deals with solving problems having not only one, but multiple, often conflicting, criteria. Such problems can arise in practically every field of science, engineering and business, and the need for efficient and reliable solution methods is increasing. The task is challenging due to the fact that, instead of a single optimal solution, multiobjective optimization results in a number of solutions with different trade-offs among criteria, also known as Pareto optimal or efficient solutions. Hence, a decision maker is needed to provide additional preference information and to identify the most satisfactory solution. Depending on the paradigm used, such information may be introduced before, during, or after the optimization process. Clearly, research and application in multiobjective optimization involve expertise in optimization as well as in decision support. This state-of-the-art survey originates from the International Seminar on Practical Approaches to Multiobjective Optimization, held in Dagstuhl Castle, Germany, in December 2006, which brought together leading experts from various contemporary multiobjective optimization fields, including evolutionary multiobjective optimization (EMO), multiple criteria decision making (MCDM) and multiple criteria decision aiding (MCDA). This book gives a unique and detailed account of the current status of research and applications in the field of multiobjective optimization. It contains 16 chapters grouped in the following 5 thematic sections: Basics on Multiobjective Optimization; Recent Interactive and Preference-Based Approaches; Visualization of Solutions; Modelling, Implementation and Applications; and Quality Assessment, Learning, and Future Challenges. |
| evolutionary multiobjective optimization theoretical advances and applications: Multiobjective Optimization Jürgen Branke, Kalyanmoy Deb, Kaisa Miettinen, Roman Słowiński, 2008 Multiobjective optimization deals with solving problems having not only one, but multiple, often conflicting, criteria. Such problems can arise in practically every field of science, engineering and business, and the need for efficient and reliable solution methods is increasing. The task is challenging due to the fact that, instead of a single optimal solution, multiobjective optimization results in a number of solutions with different trade-offs among criteria, also known as Pareto optimal or efficient solutions. Hence, a decision maker is needed to provide additional preference information and to identify the most satisfactory solution. Depending on the paradigm used, such information may be introduced before, during, or after the optimization process. Clearly, research and application in multiobjective optimization involve expertise in optimization as well as in decision support. This state-of-the-art survey originates from the International Seminar on Practical Approaches to Multiobjective Optimization, held in Dagstuhl Castle, Germany, in December 2006, which brought together leading experts from various contemporary multiobjective optimization fields, including evolutionary multiobjective optimization (EMO), multiple criteria decision making (MCDM) and multiple criteria decision aiding (MCDA). This book gives a unique and detailed account of the current status of research and applications in the field of multiobjective optimization. It contains 16 chapters grouped in the following 5 thematic sections: Basics on Multiobjective Optimization; Recent Interactive and Preference-Based Approaches; Visualization of Solutions; Modelling, Implementation and Applications; and Quality Assessment, Learning, and Future Challenges. |
| evolutionary multiobjective optimization theoretical advances and applications: Information Processing with Evolutionary Algorithms Manuel Grana, Richard J. Duro, Alicia d'Anjou, Paul P. Wang, 2005-01-05 Provides a broad sample of current information processing applications Includes examples of successful applications that will encourage practitioners to apply the techniques described in the book to real-life problems |
| evolutionary multiobjective optimization theoretical advances and applications: Intelligent Decision Systems in Large-Scale Distributed Environments Pascal Bouvry, Horacio González-Vélez, Joanna Kołodziej, 2011-06-19 One of the most challenging issues for the intelligent decision systems is to effectively manage the large-scale complex distributed environments such as computational clouds, grids, ad hoc and P2P networks, under the different types of users, their relations, and real-world uncertainties. In this context the IT resources and services usually belong to different owners (institutions, enterprises, or individuals) and are managed by different administrators. These administrators conform to different sets of rules and configuration directives, and can impose different usage policies on the system users. Additionally, uncertainties are presented in various types of information that are incomplete, imprecise, fragmentary or overloading, which hinders the full and precise determination of the evaluation criteria, their subsequent and selection, the assignment scores, and eventually the final integrated decision result. This book presents new ideas, analysis, implementations and evaluation of the next generation intelligent techniques for solving complex decision problems in large-scale distributed systems. In 15 chapters several important formulations of the decision problems in heterogeneous environments are identified and a review of the recent approaches, from game theoretical models and computational intelligent techniques, such as genetic, memetic and evolutionary algorithms, to intelligent multi-agent systems and networking are presented. We believe that this volume will serve as a reference for the students, researchers and industry practitioners working in or are interested in joining interdisciplinary works in the areas of intelligent decision systems using emergent distributed computing paradigms. It will also allow newcomers to grasp key concerns and potential solutions on the selected topics. |
| evolutionary multiobjective optimization theoretical advances and applications: Bio-inspired Computing Models And Algorithms Tao Song, Pan Zheng, Dennis Mou Ling Wong, Xun Wang, 2019-04-05 Bio-inspired computing (BIC) focuses on the designs and developments of computer algorithms and models based on biological mechanisms and living phenomena. It is now a major subfield of natural computation that leverages on the recent advances in computer science, biology and mathematics.The ideas provide abundant inspiration to construct high-performance computing models and intelligent algorithms, thus enabling powerful tools to solve real-life problems.Written by world-renowned researchers, this compendium covers the most influential topics on BIC, where the newly-obtained algorithms, developments and results are introduced and elaborated. The potential and valuable directions for further research are addressed as well. |
| evolutionary multiobjective optimization theoretical advances and applications: Handbook of AI-based Metaheuristics Anand J. Kulkarni, Patrick Siarry, 2021-09-01 At the heart of the optimization domain are mathematical modeling of the problem and the solution methodologies. The problems are becoming larger and with growing complexity. Such problems are becoming cumbersome when handled by traditional optimization methods. This has motivated researchers to resort to artificial intelligence (AI)-based, nature-inspired solution methodologies or algorithms. The Handbook of AI-based Metaheuristics provides a wide-ranging reference to the theoretical and mathematical formulations of metaheuristics, including bio-inspired, swarm-based, socio-cultural, and physics-based methods or algorithms; their testing and validation, along with detailed illustrative solutions and applications; and newly devised metaheuristic algorithms. This will be a valuable reference for researchers in industry and academia, as well as for all Master’s and PhD students working in the metaheuristics and applications domains. |
| evolutionary multiobjective optimization theoretical advances and applications: Advances in Artificial Intelligence -- IBERAMIA 2014 Ana L.C. Bazzan, Karim Pichara, 2014-11-11 This book constitutes the refereed proceedings of the 14th Ibero-American Conference on Artificial Intelligence, IBERAMIA 2014, held in Santiago de Chile, Chile, in November 2014. The 64 papers presented were carefully reviewed and selected from 136 submissions. The papers are organized in the following topical sections: knowledge engineering, knowledge representation and probabilistic reasoning; planning and scheduling; natural language processing; machine learning; fuzzy systems; knowledge discovery and data mining; bio-inspired computing; robotics; vision; multi-agent systems; agent-based modeling and simulation; AI in education, affective computing, and human-computer interaction; applications of AI; and ambient intelligence. |
| evolutionary multiobjective optimization theoretical advances and applications: Parallel Problem Solving from Nature, PPSN XI Robert Schaefer, Carlos Cotta, Joanna Kolodziej, Günter Rudolph, 2010-09-03 This book constitutes the refereed proceedings of the 11th International Conference on Parallel Problem Solving from Nature - PPSN XI, held in Kraków, Poland, in September 2010. The 131 revised full papers were carefully reviewed and selected from 232 submissions. The conference covers a wide range of topics, from evolutionary computation to swarm intelligence, from bio-inspired computing to real world applications. Machine learning and mathematical games supported by evolutionary algorithms as well as memetic, agent-oriented systems are also represented. |
| evolutionary multiobjective optimization theoretical advances and applications: Applied Optimization and Swarm Intelligence Eneko Osaba, Xin-She Yang, 2021-05-17 This book gravitates on the prominent theories and recent developments of swarm intelligence methods, and their application in both synthetic and real-world optimization problems. The special interest will be placed in those algorithmic variants where biological processes observed in nature have underpinned the core operators underlying their search mechanisms. In other words, the book centers its attention on swarm intelligence and nature-inspired methods for efficient optimization and problem solving. The content of this book unleashes a great opportunity for researchers, lecturers and practitioners interested in swarm intelligence, optimization problems and artificial intelligence. |
| evolutionary multiobjective optimization theoretical advances and applications: Simulated Evolution and Learning Xiaodong Li, Michael Kirley, Mengjie Zhang, Vic Ciesielski, Zbigniew Michalewicz, Tim Hendtlass, Kalyanmoy Deb, K. C. Tan, Jürgen Branke, 2008-12-11 This LNCS volume contains the papers presented at SEAL 2008, the 7th Int- nationalConference on Simulated Evolutionand Learning,held December 7–10, 2008, in Melbourne, Australia. SEAL is a prestigious international conference series in evolutionary computation and learning. This biennial event was ?rst held in Seoul, Korea, in 1996, and then in Canberra, Australia (1998), Nagoya, Japan (2000), Singapore (2002), Busan, Korea (2004), and Hefei, China (2006). SEAL 2008 received 140 paper submissions from more than 30 countries. After a rigorous peer-review process involving at least 3 reviews for each paper (i.e., over 420 reviews in total), the best 65 papers were selected to be presented at the conference and included in this volume, resulting in an acceptance rate of about 46%. The papers included in this volume cover a wide range of topics in simulated evolution and learning: from evolutionarylearning to evolutionary optimization, from hybrid systems to adaptive systems, from theoretical issues to real-world applications. They represent some of the latest and best research in simulated evolution and learning in the world. |
| evolutionary multiobjective optimization theoretical advances and applications: Optimization Techniques for Solving Complex Problems Enrique Alba, Christian Blum, Pedro Asasi, Coromoto Leon, Juan Antonio Gomez, 2009-02-17 Real-world problems and modern optimization techniques to solve them Here, a team of international experts brings together core ideas for solving complex problems in optimization across a wide variety of real-world settings, including computer science, engineering, transportation, telecommunications, and bioinformatics. Part One—covers methodologies for complex problem solving including genetic programming, neural networks, genetic algorithms, hybrid evolutionary algorithms, and more. Part Two—delves into applications including DNA sequencing and reconstruction, location of antennae in telecommunication networks, metaheuristics, FPGAs, problems arising in telecommunication networks, image processing, time series prediction, and more. All chapters contain examples that illustrate the applications themselves as well as the actual performance of the algorithms.?Optimization Techniques for Solving Complex Problems is a valuable resource for practitioners and researchers who work with optimization in real-world settings. |
| evolutionary multiobjective optimization theoretical advances and applications: Computational Intelligence: A Compendium John Fulcher, 2008-05-28 Computational Intelligence: A Compendium presents a well structured overview about this rapidly growing field with contributions from leading experts in Computational Intelligence. The main focus of the compendium is on applied methods, tried-and-proven as being effective to realworld problems, which is especially useful for practitioners, researchers, students and also newcomers to the field. This state-of- handbook-style book has contributions by leading experts. |
| evolutionary multiobjective optimization theoretical advances and applications: Multi-Objective Optimization Jyotsna K. Mandal, Somnath Mukhopadhyay, Paramartha Dutta, 2018-08-18 This book brings together the latest findings on efficient solutions of multi/many-objective optimization problems from the leading researchers in the field. The focus is on solving real-world optimization problems using strategies ranging from evolutionary to hybrid frameworks, and involving various computation platforms. The topics covered include solution frameworks using evolutionary to hybrid models in application areas like Analytics, Cancer Research, Traffic Management, Networks and Communications, E-Governance, Quantum Technology, Image Processing, etc. As such, the book offers a valuable resource for all postgraduate students and researchers interested in exploring solution frameworks for multi/many-objective optimization problems. |
| evolutionary multiobjective optimization theoretical advances and applications: MICAI 2006: Advances in Artificial Intelligence Alexander Gelbukh, Carlos Alberto Reyes-Garcia, 2006-11-07 This book constitutes the refereed proceedings of the 5th Mexican International Conference on Artificial Intelligence, MICAI 2006, held in Apizaco, Mexico in November 2006. It contains over 120 papers that address such topics as knowledge representation and reasoning, machine learning and feature selection, knowledge discovery, computer vision, image processing and image retrieval, robotics, as well as bioinformatics and medical applications. |
| evolutionary multiobjective optimization theoretical advances and applications: Inspired by Nature Susan Stepney, Andrew Adamatzky, 2017-10-25 This book is a tribute to Julian Francis Miller’s ideas and achievements in computer science, evolutionary algorithms and genetic programming, electronics, unconventional computing, artificial chemistry and theoretical biology. Leading international experts in computing inspired by nature offer their insights into the principles of information processing and optimisation in simulated and experimental living, physical and chemical substrates. Miller invented Cartesian Genetic Programming (CGP) in 1999, from a representation of electronic circuits he devised with Thomson a few years earlier. The book presents a number of CGP’s wide applications, including multi-step ahead forecasting, solving artificial neural networks dogma, approximate computing, medical informatics, control engineering, evolvable hardware, and multi-objective evolutionary optimisations. The book addresses in depth the technique of ‘Evolution in Materio’, a term coined by Miller and Downing, using a range of examples of experimental prototypes of computing in disordered ensembles of graphene nanotubes, slime mould, plants, and reaction diffusion chemical systems. Advances in sub-symbolic artificial chemistries, artificial bio-inspired development, code evolution with genetic programming, and using Reed-Muller expansions in the synthesis of Boolean quantum circuits add a unique flavour to the content. The book is a pleasure to explore for readers from all walks of life, from undergraduate students to university professors, from mathematicians, computer scientists and engineers to chemists and biologists. |
| evolutionary multiobjective optimization theoretical advances and applications: Simulated Evolution and Learning Lam Thu Bui, Yew Soon Ong, Nguyen Xuan Hoai, Hisao Ishibuchi, Ponnuthurai Nagaratnam Suganthan, 2012-12-02 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. |
| evolutionary multiobjective optimization theoretical advances and applications: MICAI 2009: Advances in Artificial Intelligence Arturo Hernández Aguirre, Raúl Monroy Borja, Carlos Albetro Reyes García, 2009-10-26 This book constitutes the refereed proceedings of the 8th Mexican International Conference on Artificial Intelligence, MICAI 2009, held in Guanajuato, Mexico, in November 2009. The 63 revised full papers presented together with one invited talk were carefully reviewed and selected from 215 submissions. The papers are organized in topical sections on logic and reasoning, ontologies, knowledge management and knowledge-based systems, uncertainty and probabilistic reasoning, natural language processing, data mining, machine learning, pattern recognition, computer vision and image processing, robotics, planning and scheduling, fuzzy logic, neural networks, intelligent tutoring systems, bioinformatics and medical applications, hybrid intelligent systems and evolutionary algorithms. |
| evolutionary multiobjective optimization theoretical advances and applications: Emerging Research on Swarm Intelligence and Algorithm Optimization Shi, Yuhui, 2014-07-31 Throughout time, scientists have looked to nature in order to understand and model solutions for complex real-world problems. In particular, the study of self-organizing entities, such as social insect populations, presents a new opportunity within the field of artificial intelligence. Emerging Research on Swarm Intelligence and Algorithm Optimization discusses current research analyzing how the collective behavior of decentralized systems in the natural world can be applied to intelligent system design. Discussing the application of swarm principles, optimization techniques, and key algorithms being used in the field, this publication serves as an essential reference for academicians, upper-level students, IT developers, and IT theorists. |
| evolutionary multiobjective optimization theoretical advances and applications: High Performance Programming for Soft Computing Oscar Humberto Montiel Ross, Roberto Sepulveda, 2014-02-04 This book examines the present and future of soft computer techniques. It explains how to use the latest technological tools, such as multicore processors and graphics processing units, to implement highly efficient intelligent system methods using a general purpose computer. |
| evolutionary multiobjective optimization theoretical advances and applications: Parallel Problem Solving from Nature – PPSN XVIII Michael Affenzeller, Stephan M. Winkler, Anna V. Kononova, Heike Trautmann, Tea Tušar, Penousal Machado, Thomas Bäck, 2024-09-06 This multi-volume LNCS set, LNCS 15148-15151, constitutes the refereed proceedings of the 18th International Conference on Parallel Problem Solving from Nature, PPSN 2024, held in Hagenberg, Austria, in September 2024. The 101 full papers presented in these proceedings were carefully reviewed and selected from 294 submissions. The papers presented in these four volumes are organized in the following topical sections: Part I: Combinatorial Optimization; Genetic Programming; Fitness Landscape Modeling and Analysis. Part II: Benchmarking and Performance Measures; Automated Algorithm Selection and Configuration; Numerical Optimization; Bayesian- and Surrogate-Assisted Optimization. Part III: Theoretical Aspects of Nature-Inspired Optimization; (Evolutionary) Machine Learning and Neuroevolution; Evolvable Hardware and Evolutionary Robotics. Part IV: Multi-Objective Optimization; Real-World Applications. |
| evolutionary multiobjective optimization theoretical advances and applications: Civil and Environmental Engineering: Concepts, Methodologies, Tools, and Applications Management Association, Information Resources, 2016-01-31 Civil and environmental engineers work together to develop, build, and maintain the man-made and natural environments that make up the infrastructures and ecosystems in which we live and thrive. Civil and Environmental Engineering: Concepts, Methodologies, Tools, and Applications is a comprehensive multi-volume publication showcasing the best research on topics pertaining to road design, building maintenance and construction, transportation, earthquake engineering, waste and pollution management, and water resources management and engineering. Through its broad and extensive coverage on a variety of crucial concepts in the field of civil engineering, and its subfield of environmental engineering, this multi-volume work is an essential addition to the library collections of academic and government institutions and appropriately meets the research needs of engineers, environmental specialists, researchers, and graduate-level students. |
| evolutionary multiobjective optimization theoretical advances and applications: Artificial Intelligence on Fashion and Textiles Wai Keung Wong, 2018-10-13 The book includes the Proceedings of the Artificial Intelligence on Fashion and Textiles conference 2018 which provides state-of-the-art techniques and applications of AI in the fashion and textile industries. It is essential reading for scientists, researchers and R&D professionals working in the field of AI with applications in the fashion and textile industry; managers in the fashion and textile enterprises; and anyone with an interest in the applications of AI. Over the last two decades, with the great advancement of computer technology, academic research in artificial intelligence (AI) and its applications in fashion and textile supply chain has been becoming a very hot topic and has received greater attention from both academics and industrialists. A number of AI-related techniques has been successfully employed and proven to handle the problems including fashion sales forecasting, supply chain optimization, planning and scheduling, textile material defect detection, fashion and textile image recognition, fashion image and style retrieval, human body modeling and fitting, etc. |
| evolutionary multiobjective optimization theoretical advances and applications: Manufacturing Scheduling Systems Jose M. Framinan, Rainer Leisten, Rubén Ruiz García, 2014-02-19 The book is devoted to the problem of manufacturing scheduling, which is the efficient allocation of jobs (orders) over machines (resources) in a manufacturing facility. It offers a comprehensive and integrated perspective on the different aspects required to design and implement systems to efficiently and effectively support manufacturing scheduling decisions. Obtaining economic and reliable schedules constitutes the core of excellence in customer service and efficiency in manufacturing operations. Therefore, scheduling forms an area of vital importance for competition in manufacturing companies. However, only a fraction of scheduling research has been translated into practice, due to several reasons. First, the inherent complexity of scheduling has led to an excessively fragmented field in which different sub problems and issues are treated in an independent manner as goals themselves, therefore lacking a unifying view of the scheduling problem. Furthermore, mathematical brilliance and elegance has sometimes taken preference over practical, general purpose, hands-on approaches when dealing with these problems. Moreover, the paucity of research on implementation issues in scheduling has restricted translation of valuable research insights into industry. Manufacturing Scheduling Systems: An Integrated View on Models, Methods and Tools presents the different elements constituting a scheduling system, along with an analysis the manufacturing context in which the scheduling system is to be developed. Examples and case studies from real implementations of scheduling systems are presented in order to drive the presentation of the theoretical insights. The book is intended for an ample readership including industrial engineering/operations post-graduate students and researchers, business managers, and readers seeking an introduction to the field. |
| evolutionary multiobjective optimization theoretical advances and applications: Evolutionary Multi-Criterion Optimization Ricardo H.C. Takahashi, Kalyanmoy Deb, Elizabeth F. Wanner, Salvatore Greco, 2011-03-25 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 submissions. The papers deal with fundamental questions of EMO theory, such as the development of algorithmically efficient tools for the evaluation of solution-set quality , the theoretical questions related to solution archiving and others. They report on the continuing effort in the development of algorithms, either for dealing with particular classes of problems or for new forms of processing the problem information. Almost one third of the papers is related to EMO applications in a diversity of fields. Eleven papers are devoted to promote the interaction with the related field of Multi-Criterion Decision Making (MCDM). |
| evolutionary multiobjective optimization theoretical advances and applications: GeoComputation, Second Edition Robert J. Abrahart, Linda M. See, 2014-06-23 A revision of Openshaw and Abrahart’s seminal work, GeoComputation, Second Edition retains influences of its originators while also providing updated, state-of-the-art information on changes in the computational environment. In keeping with the field’s development, this new edition takes a broader view and provides comprehensive coverage across the field of GeoComputation. See What’s New in the Second Edition: Coverage of ubiquitous computing, the GeoWeb, reproducible research, open access, and agent-based modelling Expanded chapter on Genetic Programming and a separate chapter developed on Evolutionary Algorithms Ten chapters updated by the same or new authors and eight new chapters added to reflect state of the art Each chapter is a stand-alone entity that covers a particular topic. You can simply dip in and out or read it from cover to cover. The opening chapter by Stan Openshaw has been preserved, with only a limited number of minor essential modifications having been enacted. This is not just a matter of respect. Openshaw’s work is eloquent, prophetic, and his overall message remains largely unchanged. In contrast to other books on this subject, GeoComputation: Second Edition supplies a state-of-the-art review of all major areas in GeoComputation with chapters written especially for this book by invited specialists. This approach helps develop and expand a computational culture, one that can exploit the ever-increasing richness of modern geographical and geospatial datasets. It also supplies an instructional guide to be kept within easy reach for regular access and when need arises. |
| evolutionary multiobjective optimization theoretical advances and applications: Swarm, Evolutionary, and Memetic Computing Bijaya Ketan Panigrahi, Swagatam Das, Ponnuthurai Nagaratnam Suganthan, Subhransu Sekhar Dash, 2010-12-06 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. |
| evolutionary multiobjective optimization theoretical advances and applications: Evolutionary Multi-Criterion Optimization Shigeru Obayashi, Kalyanmoy Deb, Carlo Poloni, Tomoyuki Hiroyasu, Tadahiko Murata, 2007-05-20 This book constitutes the refereed proceedings of the 4th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2007, held in Matsushima, Japan in March 2007. The 65 revised full papers presented together with 4 invited papers are organized in topical sections on algorithm design, algorithm improvements, alternative methods, applications, engineering design, many objectives, objective handling, and performance assessments. |
| evolutionary multiobjective optimization theoretical advances and applications: Multi-Objective Optimization Gade Pandu Rangaiah, 2009 Optimization has been playing a key role in the design, planning and operation of chemical and related processes for nearly half a century. Although process optimization for multiple objectives was studied by several researchers back in the 1970s and 1980s, it has attracted active research in the last 10 years, spurred by the new and effective techniques for multi-objective optimization. In order to capture this renewed interest, this monograph presents the recent and ongoing research in multi-optimization techniques and their applications in chemical engineering. Following a brief introduction and general review on the development of multi-objective optimization applications in chemical engineering since 2000, the book gives a description of selected multi-objective techniques and then goes on to discuss chemical engineering applications. These applications are from diverse areas within chemical engineering, and are presented in detail. All chapters will be of interest to researchers in multi-objective optimization and/or chemical engineering; they can be read individually and used in one''s learning and research. Several exercises are included at the end of many chapters, for use by both practicing engineers and students. |
| evolutionary multiobjective optimization theoretical advances and applications: Parallel Problem Solving from Nature - PPSN XII Carlos Coello Coello, Vincenzo Cutello, Kalyanmoy Deb, Stephanie Forrest, Giuseppe Nicosia, Mario Pavone, 2012-08-27 The two volume set LNCS 7491 and 7492 constitutes the refereed proceedings of the 12th International Conference on Parallel Problem Solving from Nature, PPSN 2012, held in Taormina, Sicily, Italy, in September 2012. The total of 105 revised full papers were carefully reviewed and selected from 226 submissions. The meeting began with 6 workshops which offered an ideal opportunity to explore specific topics in evolutionary computation, bio-inspired computing and metaheuristics. PPSN 2012 also included 8 tutorials. The papers are organized in topical sections on evolutionary computation; machine learning, classifier systems, image processing; experimental analysis, encoding, EDA, GP; multiobjective optimization; swarm intelligence, collective behavior, coevolution and robotics; memetic algorithms, hybridized techniques, meta and hyperheuristics; and applications. |
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Podcasts – Evolutionary.org
Evolutionary.org Hardcore 2.0 #169- More top Evolutionary.org logs and reviews part 2 By Euro Pharma Steve Smi 4 weeks ago
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loving dbol but too much water, what else? - evolutionary.org
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