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Search Methodologies : Introductory Tutorials in Optimization and Decision Support Techniques
Overview of attention for book
Table of Contents
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Book Overview
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Chapter 1
Introduction
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Chapter 2
Classical Techniques
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Chapter 3
Integer Programming
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Chapter 4
Genetic Algorithms
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Chapter 5
Genetic Programming
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Chapter 6
Tabu Search
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Chapter 7
Simulated Annealing
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Chapter 8
Variable Neighborhood Search
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Chapter 9
Constraint Programming
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Chapter 10
Multi-Objective Optimization
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Chapter 11
Complexity Theory and the No Free Lunch Theorem
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Chapter 12
Machine Learning
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Chapter 13
Artificial Immune Systems
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Chapter 14
Swarm Intelligence
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Chapter 15
Fuzzy Reasoning
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Chapter 16
Rough Set Based Decision Support
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Chapter 17
Hyper-Heuristics
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Chapter 18
Approximation Algorithms
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Chapter 19
Fitness Landscapes
Overall attention for this book and its chapters
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Mentioned by
twitter
2
X users
syllabi
2
institutions with syllabi
Citations
dimensions_citation
220
Dimensions
Readers on
mendeley
236
Mendeley
Book overview
1. Introduction
2. Classical Techniques
3. Integer Programming
4. Genetic Algorithms
5. Genetic Programming
6. Tabu Search
7. Simulated Annealing
8. Variable Neighborhood Search
9. Constraint Programming
10. Multi-Objective Optimization
11. Complexity Theory and the No Free Lunch Theorem
12. Machine Learning
13. Artificial Immune Systems
14. Swarm Intelligence
15. Fuzzy Reasoning
16. Rough Set Based Decision Support
17. Hyper-Heuristics
18. Approximation Algorithms
19. Fitness Landscapes
Summary
X
Syllabi
Dimensions citations
This data is correct as of December 2015 - for more up to date information, please visit
https://opensyllabus.org/
So far, Altmetric has seen this research output assigned in
2
syllabi from
2
institutions on Open Syllabus Project.
Institution
Syllabi count
Course subject areas covered
University of Nottingham
1
Unknown
Unknown
1
Unknown