Cohort Intelligence: A Socio-inspired Optimization Method
Authors: Kulkarni, Anand Jayant, Krishnasamy, Ganesh, Abraham, Ajith
Free Preview- Presents the core and underlying principles and analysis of the different concepts associated with an emerging socio-inspired AI optimization tool referred to as Cohort Intelligence (CI)
- Discusses in detail the Cohort Intelligence methodology as well as several modifications for solving a variety of problems
- Demonstrates the ability of Cohort Intelligence methodology for solving several cases of the combinatorial problems such as Traveling Salesman Problem (TSP) and Knapsack Problem (KP)
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- About this book
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This Volume discusses the underlying principles and analysis of the different concepts associated with an emerging socio-inspired optimization tool referred to as Cohort Intelligence (CI). CI algorithms have been coded in Matlab and are freely available from the link provided inside the book. The book demonstrates the ability of CI methodology for solving combinatorial problems such as Traveling Salesman Problem and Knapsack Problem in addition to real world applications from the healthcare, inventory, supply chain optimization and Cross-Border transportation. The inherent ability of handling constraints based on probability distribution is also revealed and proved using these problems.
- Table of contents (10 chapters)
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Introduction to Optimization
Pages 1-7
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Socio-Inspired Optimization Using Cohort Intelligence
Pages 9-24
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Cohort Intelligence for Constrained Test Problems
Pages 25-37
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Modified Cohort Intelligence for Solving Machine Learning Problems
Pages 39-54
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Solution to 0–1 Knapsack Problem Using Cohort Intelligence Algorithm
Pages 55-74
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Table of contents (10 chapters)
- Download Preface 1 PDF (47.5 KB)
- Download Sample pages 2 PDF (534 KB)
- Download Table of contents PDF (116.2 KB)
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Bibliographic Information
- Bibliographic Information
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- Book Title
- Cohort Intelligence: A Socio-inspired Optimization Method
- Authors
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- Anand Jayant Kulkarni
- Ganesh Krishnasamy
- Ajith Abraham
- Series Title
- Intelligent Systems Reference Library
- Series Volume
- 114
- Copyright
- 2017
- Publisher
- Springer International Publishing
- Copyright Holder
- Springer International Publishing Switzerland
- eBook ISBN
- 978-3-319-44254-9
- DOI
- 10.1007/978-3-319-44254-9
- Hardcover ISBN
- 978-3-319-44253-2
- Softcover ISBN
- 978-3-319-83022-3
- Series ISSN
- 1868-4394
- Edition Number
- 1
- Number of Pages
- XI, 134
- Number of Illustrations
- 29 b/w illustrations
- Topics
