Evolutionary Computation For Dynamic Optimization Problems
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Evolutionary Computation For Dynamic Optimization Problems
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Author : Shengxiang Yang
language : en
Publisher: Springer
Release Date : 2013-11-18
Evolutionary Computation For Dynamic Optimization Problems written by Shengxiang Yang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-18 with Technology & Engineering categories.
This book provides a compilation on the state-of-the-art and recent advances of evolutionary computation for dynamic optimization problems. The motivation for this book arises from the fact that many real-world optimization problems and engineering systems are subject to dynamic environments, where changes occur over time. Key issues for addressing dynamic optimization problems in evolutionary computation, including fundamentals, algorithm design, theoretical analysis, and real-world applications, are presented. "Evolutionary Computation for Dynamic Optimization Problems" is a valuable reference to scientists, researchers, professionals and students in the field of engineering and science, particularly in the areas of computational intelligence, nature- and bio-inspired computing, and evolutionary computation.
Advances In Evolutionary Computing
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Author : Ashish Ghosh
language : en
Publisher: Springer Science & Business Media
Release Date : 2002-11-26
Advances In Evolutionary Computing written by Ashish Ghosh and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-11-26 with Computers categories.
This book provides a collection of fourty articles containing new material on both theoretical aspects of Evolutionary Computing (EC), and demonstrating the usefulness/success of it for various kinds of large-scale real world problems. Around 23 articles deal with various theoretical aspects of EC and 17 articles demonstrate the success of EC methodologies. These articles are written by leading experts of the field from different countries all over the world.
Evolutionary Optimization In Dynamic Environments
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Author : Jürgen Branke
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Evolutionary Optimization In Dynamic Environments written by Jürgen Branke and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
Evolutionary Algorithms (EAs) have grown into a mature field of research in optimization, and have proven to be effective and robust problem solvers for a broad range of static real-world optimization problems. Yet, since they are based on the principles of natural evolution, and since natural evolution is a dynamic process in a changing environment, EAs are also well suited to dynamic optimization problems. Evolutionary Optimization in Dynamic Environments is the first comprehensive work on the application of EAs to dynamic optimization problems. It provides an extensive survey on research in the area and shows how EAs can be successfully used to continuously and efficiently adapt a solution to a changing environment, find a good trade-off between solution quality and adaptation cost, find robust solutions whose quality is insensitive to changes in the environment, find flexible solutions which are not only good but that can be easily adapted when necessary. All four aspects are treated in this book, providing a holistic view on the challenges and opportunities when applying EAs to dynamic optimization problems. The comprehensive and up-to-date coverage of the subject, together with details of latest original research, makes Evolutionary Optimization in Dynamic Environments an invaluable resource for researchers and professionals who are dealing with dynamic and stochastic optimization problems, and who are interested in applying local search heuristics, such as evolutionary algorithms.
Cellular Learning Automata Theory And Applications
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Author : Reza Vafashoar
language : en
Publisher: Springer Nature
Release Date : 2020-07-24
Cellular Learning Automata Theory And Applications written by Reza Vafashoar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-24 with Technology & Engineering categories.
This book highlights both theoretical and applied advances in cellular learning automata (CLA), a type of hybrid computational model that has been successfully employed in various areas to solve complex problems and to model, learn, or simulate complicated patterns of behavior. Owing to CLA’s parallel and learning abilities, it has proven to be quite effective in uncertain, time-varying, decentralized, and distributed environments. The book begins with a brief introduction to various CLA models, before focusing on recently developed CLA variants. In turn, the research areas related to CLA are addressed as bibliometric network analysis perspectives. The next part of the book presents CLA-based solutions to several computer science problems in e.g. static optimization, dynamic optimization, wireless networks, mesh networks, and cloud computing. Given its scope, the book is well suited for all researchers in the fields of artificial intelligence and reinforcement learning.
Evolutionary Design And Manufacture
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Author : I.C. Parmee
language : en
Publisher: Springer Science & Business Media
Release Date : 2000-04-12
Evolutionary Design And Manufacture written by I.C. Parmee and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-04-12 with Computers categories.
This collection of selected papers from the Fourth International Conference on Adaptive Computing in Design and Manufacture (ACDM0) represents a cross-section of the state-of-the art relating to the integration of advanced stochastic search, exploration and optimisation techniques with complex problem areas relating to various aspects of design and manufacturing processes. The Conference, held in the Sherwell Conference Centre at the University of Plymouth, Devon, UK in April, 2000, is a well-established biennial event supported by several UK Engineering Institutions and recognised by the International Society for Genetic and Evolutionary Computation as a mainstream event. The conference continues to attract an international audience of leading researchers and practitioners in the field. Aerospace, mechanical, thermal and structural design are among the subjects treated. In terms of manufacturing processes, cell formation, facility design, system control and robotics are addressed. In most cases, results from their application to or integration with real-world industrial problems are very much in evidence and conclusions relating to the overall utility of the various techniques across a diverse spectrum of problem areas are available. Evolutionary computing research and its application provides the mainstay in the great majority of papers. In the tradition of the ACDM series, papers utilising neural computing technologies and related computational intelligence techniques within the design/manufacture environments have also been included. The collection further illustrates the increasing uptake of these technologies in terms of academic research, academic and industrial collaboration and industrial practice. It is apparent that application strategies are becoming increasingly sophisticated as the powerful data processing capabilities of the technologies become more apparent and their increasing potential leads to integration with more complex problem areas so the book will be of particular interest to both design and computer science research communities in addition to those industrial organisations that are either already including these technologies in day-to-day working practice or that wish to familiarise themselves with the potential utility of their application further.
Evolutionary Computation In Dynamic And Uncertain Environments
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Author : Shengxiang Yang
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-03-07
Evolutionary Computation In Dynamic And Uncertain Environments written by Shengxiang Yang and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-03-07 with Mathematics categories.
This book compiles recent advances of evolutionary algorithms in dynamic and uncertain environments within a unified framework. The book is motivated by the fact that some degree of uncertainty is inevitable in characterizing any realistic engineering systems. Discussion includes representative methods for addressing major sources of uncertainties in evolutionary computation, including handle of noisy fitness functions, use of approximate fitness functions, search for robust solutions, and tracking moving optimums.
Evolutionary Algorithms And Dynamic Optimization Problems
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Author : Karsten Weicker
language : en
Publisher:
Release Date : 2003
Evolutionary Algorithms And Dynamic Optimization Problems written by Karsten Weicker and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with categories.
Evolutionary Optimization Algorithms
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Author : Dan Simon
language : en
Publisher: John Wiley & Sons
Release Date : 2013-06-13
Evolutionary Optimization Algorithms written by Dan Simon and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-13 with Mathematics categories.
A clear and lucid bottom-up approach to the basic principles of evolutionary algorithms Evolutionary algorithms (EAs) are a type of artificial intelligence. EAs are motivated by optimization processes that we observe in nature, such as natural selection, species migration, bird swarms, human culture, and ant colonies. This book discusses the theory, history, mathematics, and programming of evolutionary optimization algorithms. Featured algorithms include genetic algorithms, genetic programming, ant colony optimization, particle swarm optimization, differential evolution, biogeography-based optimization, and many others. Evolutionary Optimization Algorithms: Provides a straightforward, bottom-up approach that assists the reader in obtaining a clear but theoretically rigorous understanding of evolutionary algorithms, with an emphasis on implementation Gives a careful treatment of recently developed EAs including opposition-based learning, artificial fish swarms, bacterial foraging, and many others and discusses their similarities and differences from more well-established EAs Includes chapter-end problems plus a solutions manual available online for instructors Offers simple examples that provide the reader with an intuitive understanding of the theory Features source code for the examples available on the author's website Provides advanced mathematical techniques for analyzing EAs, including Markov modeling and dynamic system modeling Evolutionary Optimization Algorithms: Biologically Inspired and Population-Based Approaches to Computer Intelligence is an ideal text for advanced undergraduate students, graduate students, and professionals involved in engineering and computer science.
Evolutionary Computation In Scheduling
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Author : Amir H. Gandomi
language : en
Publisher: John Wiley & Sons
Release Date : 2020-05-19
Evolutionary Computation In Scheduling written by Amir H. Gandomi and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-19 with Mathematics categories.
Presents current developments in the field of evolutionary scheduling and demonstrates the applicability of evolutionary computational techniques to solving scheduling problems This book provides insight into the use of evolutionary computations (EC) in real-world scheduling, showing readers how to choose a specific evolutionary computation and how to validate the results using metrics and statistics. It offers a spectrum of real-world optimization problems, including applications of EC in industry and service organizations such as healthcare scheduling, aircraft industry, school timetabling, manufacturing systems, and transportation scheduling in the supply chain. It also features problems with different degrees of complexity, practical requirements, user constraints, and MOEC solution approaches. Evolutionary Computation in Scheduling starts with a chapter on scientometric analysis to analyze scientific literature in evolutionary computation in scheduling. It then examines the role and impacts of ant colony optimization (ACO) in job shop scheduling problems, before presenting the application of the ACO algorithm in healthcare scheduling. Other chapters explore task scheduling in heterogeneous computing systems and truck scheduling using swarm intelligence, application of sub-population scheduling algorithm in multi-population evolutionary dynamic optimization, task scheduling in cloud environments, scheduling of robotic disassembly in remanufacturing using the bees algorithm, and more. This book: Provides a representative sampling of real-world problems currently being tackled by practitioners Examines a variety of single-, multi-, and many-objective problems that have been solved using evolutionary computations, including evolutionary algorithms and swarm intelligence Consists of four main parts: Introduction to Scheduling Problems, Computational Issues in Scheduling Problems, Evolutionary Computation, and Evolutionary Computations for Scheduling Problems Evolutionary Computation in Scheduling is ideal for engineers in industries, research scholars, advanced undergraduates and graduate students, and faculty teaching and conducting research in Operations Research and Industrial Engineering.
Evolutionary Optimization
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Author : Ruhul Sarker
language : en
Publisher: Springer Science & Business Media
Release Date : 2002-01-31
Evolutionary Optimization written by Ruhul Sarker and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-01-31 with Business & Economics categories.
The use of evolutionary computation techniques has grown considerably over the past several years. Over this time, the use and applications of these techniques have been further enhanced resulting in a set of computational intelligence (also known as modern heuristics) tools that are particularly adept for solving complex optimization problems. Moreover, they are characteristically more robust than traditional methods based on formal logics or mathematical programming for many real world OR/MS problems. Hence, evolutionary computation techniques have dealt with complex optimization problems better than traditional optimization techniques although they can be applied to easy and simple problems where conventional techniques work well. Clearly there is a need for a volume that both reviews state-of-the-art evolutionary computation techniques, and surveys the most recent developments in their use for solving complex OR/MS problems. This volume on Evolutionary Optimization seeks to fill this need. Evolutionary Optimization is a volume of invited papers written by leading researchers in the field. All papers were peer reviewed by at least two recognized reviewers. The book covers the foundation as well as the practical side of evolutionary optimization.