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Evolutionary Constrained Optimization

Overview of attention for book
Cover of 'Evolutionary Constrained Optimization'

Table of Contents

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    Book Overview
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    Chapter 1 A Critical Review of Adaptive Penalty Techniques in Evolutionary Computation
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    Chapter 2 Ruggedness Quantifying for Constrained Continuous Fitness Landscapes
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    Chapter 3 Trust Regions in Surrogate-Assisted Evolutionary Programming for Constrained Expensive Black-Box Optimization
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    Chapter 4 Ephemeral Resource Constraints in Optimization
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    Chapter 5 Incremental Approximation Models for Constrained Evolutionary Optimization
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    Chapter 6 Efficient Constrained Optimization by the $$\varepsilon $$ ε Constrained Differential Evolution with Rough Approximation
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    Chapter 7 Analyzing the Behaviour of Multi-recombinative Evolution Strategies Applied to a Conically Constrained Problem
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    Chapter 8 Locating Potentially Disjoint Feasible Regions of a Search Space with a Particle Swarm Optimizer
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    Chapter 9 Ensemble of Constraint Handling Techniques for Single Objective Constrained Optimization
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    Chapter 10 Evolutionary Constrained Optimization: A Hybrid Approach
Attention for Chapter 1: A Critical Review of Adaptive Penalty Techniques in Evolutionary Computation
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Citations

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Chapter title
A Critical Review of Adaptive Penalty Techniques in Evolutionary Computation
Chapter number 1
Book title
Evolutionary Constrained Optimization
Published by
Springer, New Delhi, January 2015
DOI 10.1007/978-81-322-2184-5_1
Book ISBNs
978-8-13-222183-8, 978-8-13-222184-5
Authors

Helio J. C. Barbosa, Afonso C. C. Lemonge, Heder S. Bernardino

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 38%
Student > Master 3 38%
Unknown 2 25%
Readers by discipline Count As %
Computer Science 3 38%
Engineering 2 25%
Medicine and Dentistry 1 13%
Unknown 2 25%

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