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Evolutionary Constrained Optimization

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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 6: Efficient Constrained Optimization by the $$\varepsilon $$ ε Constrained Differential Evolution with Rough Approximation
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Chapter title
Efficient Constrained Optimization by the $$\varepsilon $$ ε Constrained Differential Evolution with Rough Approximation
Chapter number 6
Book title
Evolutionary Constrained Optimization
Published by
Springer, New Delhi, January 2015
DOI 10.1007/978-81-322-2184-5_6
Book ISBNs
978-8-13-222183-8, 978-8-13-222184-5
Authors

Tetsuyuki Takahama, Setsuko Sakai

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