Success in evolutionary computation
- Ang Yang, Yin Shan, Lam Thu Bui (eds.).
- English. English.
- text file
- Berlin : Springer, ©2008.
- Physical description
- 1 online resource (viii, 372 pages) : illustrations
- Studies in computational intelligence ; 92. 1860-949X
- Includes bibliographical references.
- Part I Theory.- Adaptation of a Success Story in GAs: Estimation-of-Distribution Algorithms for Tree-based Optimization Problems.- The Automated Design of Artificial Neural Networks Using Evolutionary Computation.- A Versatile Surrogate-Assisted Memetic Algorithm for Optimization of Computationally.- Expensive Functions and its Engineering Applications.- Data Mining and Intelligent Multi Agent Technologies in Medical Informatics.- Part II Applications.- Evolving Trading Rules.- A hybrid genetic algorithm for the protein folding problem using the 2D-HP lattice model.- Optimal Management of Agricultural Systems.- Evolutionary Electronics: Automatic Synthesis of Analog Circuits by Gas.- Intuitive Visualization and Interactive Analysis of Pareto Sets Applied on Production Engineering Systems.- Privacy Protection with Genetic Algorithms.- A revision of Evolutionary Computation techniques in telecommunications and an application for the network global planning problem.- Survivable Network Design with an Evolution Strategy.- Evolutionary Computations for Design Optimization and Test Automation in VLSI Circuits.- Evolving Cooperative Agents in Economy Market using Genetic Algorithms.- Optimizing Multiplicative General Parameter Finite Impulse Response Filters Using Evolutionary Computation.- Applying Genetic Algorithms to optimize the cost of multiple sourcing supply chain systems-An industry case study.
- (source: Nielsen Book Data)
- Publisher's summary
Darwinian evolutionary theory is one of the most important theories in human history for it has equipped us with a valuable tool to understand the amazing world around us. There can be little surprise, therefore, that Evolutionary Computation (EC), inspired by natural evolution, has been so successful in providing high quality solutions in a large number of domains. EC includes a number of techniques, such as Genetic Algorithms, Genetic Programming, Evolution Strategy and Evolutionary Programming, which have been used in a diverse range of highly successful applications. This book brings together some of these EC applications in fields including electronics, telecommunications, health, bioinformatics, supply chain and other engineering domains, to give the audience, including both EC researchers and practitioners, a glimpse of this exciting rapidly evolving field.
(source: Nielsen Book Data)
- Publication date
- Studies in computational intelligence, 1860-949X ; 92
- 9783540762867 (electronic bk.)
- 3540762868 (electronic bk.)
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