Designing Evolutionary Algorithms for Dynamic Environments
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Beschreibung
The robust capability of evolutionary algorithms (EAs) to find solutions to difficult problems has permitted them to become popular as optimization and search techniques for many industries. Despite the success of EAs, the resultant solutions are often fragile and prone to failure when the problem changes, usually requiring human intervention to keep the EA on track. Since many optimization problems in engineering, finance, and information technology require systems that can adapt to changes over time, it is desirable that EAs be able to respond to changes in the environment on their own. This book provides an analysis of what an EA needs to do to automatically and continuously solve dynamic problems, focusing on detecting changes in the problem environment and responding to those changes. In this book we identify and quantify a key attribute needed to improve the detection and response performance of EAs in dynamic environments. We then create an enhanced EA, designed explicitly to exploit this new understanding. This enhanced EA is shown to have superior performance on some types of problems. Our experiments evaluating this enhanced EA indicate some pre viously unknown relationships between performance and diversity that may lead to general methods for improving EAs in dynamic environments. Along the way, several other important design issues are addressed involving com putational efficiency, performance measurement, and the testing of EAs in dynamic environments.
The first book focusing on robustness, stability, and performance of EAs in dynamic environments Includes supplementary material: sn.pub/extras
The robust capability of Evolutionary Algorithms (EAs) to find solutions to difficult problems has permitted them to become the optimization and search techniques of choice for many practical static problems. Despite this success in many different environments, EAs are often prone to failure when subjected to even small changes in the problem. This book addresses the issues involved in the design of EAs that successfully operate in dynamic environments without human intervention, and provides a method for creating EAs for these environments.
Autor*in
Ronald W. Morrison
Themen in »Designing Evolutionary Algorithms for Dynamic Environments«
Adaptive Algorithms Dynamic Systems Evolutionary Algorithms Evolutionary Programming Fitness Landscapes Genetic Algorithms Heuristics Immune Systems Optimization Problem Solving Systems Evolution algorithms evolutionary algorithm
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From the reviews:
"This book is a monograph explaining the research performed by the author in the field of dynamic search algorithms. … Overall, the work is presented in a clear manner and gives a useful introduction to what is likely to be a major area of development in the field of evolutionary algorithms. I would definitely recommend the book to all workers in this field who want a clear but rapid overview … ." (G. F. Page, Robotica, Vol. 24, 2006)
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