Cohort Intelligence: A Socio-inspired Optimization Method

Anand Jayant Kulkarni

ISBN 10: 3319830228 / ISBN 13: 9783319830223

Verlag: Springer, Berlin, Springer International Publishing, Springer, 2018

Beschreibung

Druck auf Anfrage Neuware - Printed after ordering - 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.

Bestandsnummer des Verkäufers 9783319830223

Bibliografische Details

• Titel: Cohort Intelligence: A Socio-inspired Optimization Method
• Verlag: Springer, Berlin, Springer International Publishing, Springer
• Erscheinungsjahr: 2018
• Sprache: Englisch
• ISBN-10: 3319830228
• ISBN-13: 9783319830223
• Einband: Taschenbuch
• Zustand: Neu
• Abmessungen: 235B x 155 H x 8 T Millimeter Breite: 235 mm, Höhe: 155 mm, Tiefe: 8 mm
• Gewicht: 237 Gramm

Über diesen Titel

Inhaltsangabe

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.