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Kirjailija

Ganesh Krishnasamy

Kirjat ja teokset yhdessä paikassa: 2 kirjaa, julkaisuja vuosilta 2016–2018, suosituimpiin kuuluu Cohort Intelligence: A Socio-inspired Optimization Method. Vertaile teosten hintoja ja tarkista saatavuus suomalaisista kirjakaupoista.

2 kirjaa

Kirjojen julkaisuvuodet: 2016–2018.

Cohort Intelligence: A Socio-inspired Optimization Method

Cohort Intelligence: A Socio-inspired Optimization Method

Anand Jayant Kulkarni; Ganesh Krishnasamy; Ajith Abraham

Springer International Publishing AG
2018
nidottu
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.
Cohort Intelligence: A Socio-inspired Optimization Method

Cohort Intelligence: A Socio-inspired Optimization Method

Anand Jayant Kulkarni; Ganesh Krishnasamy; Ajith Abraham

Springer International Publishing AG
2016
sidottu
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.