Authors:
- 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)
- Includes supplementary material: sn.pub/extras
Part of the book series: Intelligent Systems Reference Library (ISRL, volume 114)
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Table of contents (10 chapters)
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Front Matter
About this book
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.
Authors and Affiliations
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Odette School of Business, University of Windsor Odette School of Business, Windsor, Canada
Anand Jayant Kulkarni
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Department of Electrical Engineering, Faculty of Engineering, Universiti Malaya , Kuala Lumpur, Malaysia
Ganesh Krishnasamy
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Scientific Network for Inn and Res Exc, Machine Intell Research Labs (MIR labs) Scientific Network for Inn and Res Exc, Auburn, WA, USA
Ajith Abraham
Bibliographic Information
Book Title: Cohort Intelligence: A Socio-inspired Optimization Method
Authors: Anand Jayant Kulkarni, Ganesh Krishnasamy, Ajith Abraham
Series Title: Intelligent Systems Reference Library
DOI: https://doi.org/10.1007/978-3-319-44254-9
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing Switzerland 2017
Hardcover ISBN: 978-3-319-44253-2Published: 03 October 2016
Softcover ISBN: 978-3-319-83022-3Published: 15 June 2018
eBook ISBN: 978-3-319-44254-9Published: 22 September 2016
Series ISSN: 1868-4394
Series E-ISSN: 1868-4408
Edition Number: 1
Number of Pages: XI, 134
Number of Illustrations: 29 b/w illustrations