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Evolutionary Computation for Dynamic Optimization Problems

Overview of attention for book
Cover of 'Evolutionary Computation for Dynamic Optimization Problems'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Evolutionary Dynamic Optimization: Test and Evaluation Environments
  3. Altmetric Badge
    Chapter 2 Evolutionary Dynamic Optimization: Methodologies
  4. Altmetric Badge
    Chapter 3 Evolutionary Dynamic Optimization: Challenges and Perspectives
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    Chapter 4 Dynamic Multi-objective Optimization: A Survey of the State-of-the-Art
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    Chapter 5 A Comparative Study on Particle Swarm Optimization in Dynamic Environments
  7. Altmetric Badge
    Chapter 6 Memetic Algorithms for Dynamic Optimization Problems
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    Chapter 7 BIPOP: A New Algorithm with Explicit Exploration/Exploitation Control for Dynamic Optimization Problems
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    Chapter 8 Evolutionary Optimization on Continuous Dynamic Constrained Problems - An Analysis
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    Chapter 9 Theoretical Advances in Evolutionary Dynamic Optimization
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    Chapter 10 Analyzing Evolutionary Algorithms for Dynamic Optimization Problems Based on the Dynamical Systems Approach
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    Chapter 11 Dynamic Fitness Landscape Analysis
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    Chapter 12 Dynamics in the Multi-objective Subset Sum: Analysing the Behavior of Population Based Algorithms
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    Chapter 13 Ant Colony Optimization Algorithms with Immigrants Schemes for the Dynamic Travelling Salesman Problem
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    Chapter 14 Genetic Algorithms for Dynamic Routing Problems in Mobile Ad Hoc Networks
  16. Altmetric Badge
    Chapter 15 Evolutionary Computation for Dynamic Capacitated Arc Routing Problem
  17. Altmetric Badge
    Chapter 16 Evolutionary Algorithms for the Multiple Unmanned Aerial Combat Vehicles Anti-ground Attack Problem in Dynamic Environments
  18. Altmetric Badge
    Chapter 17 Advanced Planning in Vertically Integrated Wine Supply Chains
Attention for Chapter 2: Evolutionary Dynamic Optimization: Methodologies
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Chapter title
Evolutionary Dynamic Optimization: Methodologies
Chapter number 2
Book title
Evolutionary Computation for Dynamic Optimization Problems
Published in
Studies in Computational Intelligence, February 2016
DOI 10.1007/978-3-642-38416-5_2
Book ISBNs
978-3-64-238415-8, 978-3-64-238416-5
Authors

Trung Thanh Nguyen, Shengxiang Yang, Juergen Branke, Xin Yao

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 24%
Professor > Associate Professor 3 18%
Student > Bachelor 2 12%
Professor 2 12%
Lecturer > Senior Lecturer 1 6%
Other 2 12%
Unknown 3 18%
Readers by discipline Count As %
Computer Science 9 53%
Nursing and Health Professions 1 6%
Mathematics 1 6%
Decision Sciences 1 6%
Engineering 1 6%
Other 0 0%
Unknown 4 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 February 2015.
All research outputs
#21,160,107
of 25,992,468 outputs
Outputs from Studies in Computational Intelligence
#1
of 1 outputs
Outputs of similar age
#303,209
of 408,447 outputs
Outputs of similar age from Studies in Computational Intelligence
#1
of 1 outputs
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So far Altmetric has tracked 1 research outputs from this source. They receive a mean Attention Score of 0.5. This one scored the same or higher as 0 of them.
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