Cohort Intelligence: A Socio-inspired Optimization Method: Intelligent Systems Reference Library, cartea 114
Autor Anand Jayant Kulkarni, Ganesh Krishnasamy, Ajith Abrahamen Limba Engleză Hardback – 3 oct 2016
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Specificații
ISBN-13: 9783319442532
ISBN-10: 3319442538
Pagini: 102
Ilustrații: XI, 134 p. 29 illus.
Dimensiuni: 155 x 235 x 10 mm
Greutate: 0.41 kg
Ediția:1st ed. 2017
Editura: Springer International Publishing
Colecția Springer
Seria Intelligent Systems Reference Library
Locul publicării:Cham, Switzerland
ISBN-10: 3319442538
Pagini: 102
Ilustrații: XI, 134 p. 29 illus.
Dimensiuni: 155 x 235 x 10 mm
Greutate: 0.41 kg
Ediția:1st ed. 2017
Editura: Springer International Publishing
Colecția Springer
Seria Intelligent Systems Reference Library
Locul publicării:Cham, Switzerland
Cuprins
Introduction To Optimization.- Socio-Inspired Optimization Using Cohort Intelligence.- Cohort Intelligence For Constrained Test Problems.- Modified Cohort Intelligence For Solving Machine Learning Problems.- Solution To 0-1 Knapsack Problem Using Cohort Intelligence Algorithm.- Cohort Intelligence For Solving Travelling Salesman Problems.- Solution To A New Variant Of The Assignment Problem Using Cohort Intelligence Algorithm.- Solution To Sea Cargo Mix (Scm) Problem Using Cohort Intelligence Algorithm.- Solution To The Selection Of Cross-Border Shippers (Scbs) Problem.- Conclusions And Future Directions.
Textul de pe ultima copertă
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.
Caracteristici
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