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Foundations of Computational Intelligence Volume 3

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Table of Contents

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    Book Overview
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    Chapter 1 Genetic Algorithms for the Use in Combinatorial Problems
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    Chapter 2 Bacterial Foraging Optimization Algorithm: Theoretical Foundations, Analysis, and Applications
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    Chapter 3 Global Optimization Using Harmony Search: Theoretical Foundations and Applications
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    Chapter 4 Hybrid GRASP Heuristics
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    Chapter 5 Particle Swarm Optimization: Performance Tuning and Empirical Analysis
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    Chapter 6 Tabu Search to Solve Real-Life Combinatorial Optimization Problems: A Case of Study
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    Chapter 7 Reformulations in Mathematical Programming: A Computational Approach
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    Chapter 8 Graph-Based Local Elimination Algorithms in Discrete Optimization
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    Chapter 9 Evolutionary Approach to Solving Non-stationary Dynamic Multi-Objective Problems
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    Chapter 10 Turbulent Particle Swarm Optimization Using Fuzzy Parameter Tuning
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    Chapter 11 An Evolutionary Approximation for the Coefficients of Decision Functions within a Support Vector Machine Learning Strategy
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    Chapter 12 Evolutionary Computing in Statistical Data Analysis
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    Chapter 13 Meta-heuristics for System Design Engineering
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    Chapter 14 Transgenetic Algorithm: A New Endosymbiotic Approach for Evolutionary Algorithms
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    Chapter 15 Multi-objective Team Forming Optimization for Integrated Product Development Projects
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    Chapter 16 Genetic Algorithms for Task Scheduling Problem
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    Chapter 17 PSO_Bounds: A New Hybridization Technique of PSO and EDAs
Attention for Chapter 14: Transgenetic Algorithm: A New Endosymbiotic Approach for Evolutionary Algorithms
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Citations

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Chapter title
Transgenetic Algorithm: A New Endosymbiotic Approach for Evolutionary Algorithms
Chapter number 14
Book title
Foundations of Computational Intelligence Volume 3
Published by
Springer, Berlin, Heidelberg, January 2009
DOI 10.1007/978-3-642-01085-9_14
Book ISBNs
978-3-64-201084-2, 978-3-64-201085-9
Authors

Elizabeth F. Gouvêa Goldbarg, Marco C. Goldbarg, Goldbarg, Elizabeth F. Gouvêa, Goldbarg, Marco C.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Professor 3 43%
Student > Ph. D. Student 2 29%
Researcher 1 14%
Student > Doctoral Student 1 14%
Readers by discipline Count As %
Business, Management and Accounting 2 29%
Computer Science 2 29%
Agricultural and Biological Sciences 1 14%
Neuroscience 1 14%
Unknown 1 14%