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Recent Advances in Memetic Algorithms

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Cover of 'Recent Advances in Memetic Algorithms'

Table of Contents

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    Book Overview
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    Chapter 1 Memetic Evolutionary Algorithms
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    Chapter 2 An Evolutionary Approach for the Maximum Diversity Problem
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    Chapter 3 Multimeme Algorithms Using Fuzzy Logic Based Memes For Protein Structure Prediction
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    Chapter 4 A Memetic Algorithm Solving the VRP, the CARP and General Routing Problems with Nodes, Edges and Arcs
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    Chapter 5 Using Memetic Algorithms for Optimal Calibration of Automotive Internal Combustion Engines
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    Chapter 6 The Co-Evolution of Memetic Algorithms for Protein Structure Prediction
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    Chapter 7 Hybrid Evolutionary Approaches to Terminal Assignment in Communications Networks
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    Chapter 8 Effective Exploration & Exploitation of the Solution Space via Memetic Algorithms for the Circuit Partition Problem
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    Chapter 9 Towards Robust Memetic Algorithms
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    Chapter 10 NK -Fitness Landscapes and Memetic Algorithms with Greedy Operators and k -opt Local Search
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    Chapter 11 Self-Assembling of Local Searchers in Memetic Algorithms
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    Chapter 12 Designing Efficient Genetic and Evolutionary Algorithm Hybrids
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    Chapter 13 The Design of Memetic Algorithms for Scheduling and Timetabling Problems
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    Chapter 14 Memetic Algorithms for Multiobjective Optimization: Issues, Methods and Prospects
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    Chapter 15 A Memetic Learning Classifier System for Describing Continuous-Valued Problem Spaces
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    Chapter 16 Angels & Mortals: A New Combinatorial Optimization Algorithm
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Citations

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Title
Recent Advances in Memetic Algorithms
Published by
Springer Berlin Heidelberg, June 2006
DOI 10.1007/3-540-32363-5
ISBNs
978-3-54-022904-9, 978-3-54-032363-1
Editors

Hart, William E., Smith, J. E., Krasnogor, N.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Portugal 1 1%
Germany 1 1%
Austria 1 1%
Brazil 1 1%
Spain 1 1%
Unknown 76 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 23%
Student > Master 9 11%
Student > Bachelor 8 10%
Researcher 8 10%
Student > Doctoral Student 7 9%
Other 22 27%
Unknown 8 10%
Readers by discipline Count As %
Computer Science 27 33%
Engineering 25 31%
Business, Management and Accounting 6 7%
Agricultural and Biological Sciences 4 5%
Mathematics 3 4%
Other 6 7%
Unknown 10 12%