Asian Science Citation Index is committed to provide an authoritative, trusted and significant information by the coverage of the most important and influential journals to meet the needs of the global scientific community.  
ASCI Database
308-Lasani Town,
Sargodha Road,
Faisalabad, Pakistan
Fax: +92-41-8815544
Contact Via Web
Suggest a Journal
Journal of Engineering and Applied Sciences
Year: 2017  |  Volume: 12  |  Issue: 2 SI  |  Page No.: 6219 - 6222

A Collective Study on Popular Nature Inspired Optimization

Somya Sneh, Srikar Kompella and S. Chethan    

Abstract: The two subsets of nature inspired algorithms are swarm intelligence based and Bio-inspired algorithms. Swarm intelligence based algorithms behave as a sub set for Bio-inspired algorithms. Some other sources of inspiration are Physics-based Chemistry-based algorithms. Though not all of them are particularly efficient however, some of them have become popular tools for modelling and solving real world problems. The purpose of this review is to present a brief description about the four major types of swarm intelligent based algorithms along with their applications so as to provide a comprehensive view on their functioning and performance. The algorithms covered in this study are Particle Swarm Optimisation (PSO), Ant Colony System (ACS), the Artificial Bee Colony (ABC), Cuckoo Search (CS).

Fulltext    |   Related Articles   |   Back
   
 
 
 
  Related Articles

 
 
 
 
 
 
 
 
 
Copyright   |   Desclaimer   |    Privacy Policy   |   Browsers   |   Accessibility