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A Novel Approach of Image Ranking based on Enhanced Artificial Bee Colony Algorithm


Foram Joshi , Noble Group of Institution, Gujarat, India; Nidhi Gondalia, Noble Group of Institution, Gujarat, India; Nirali Mankad, Noble Group of Institution, Gujarat, India


Swarm Intelligence, Artificial Bee colony Algorithm, ranking techniques.


In recent years researchers have provided novel problem solving techniques based on swarm intelligence for solving difficult real world problems such as traffic, routing, networking, games, industries and economics. Artificial bee colony algorithm (ABC) was first developed by Dervis Karaboga [1]. When the robust performance is desired by means of searching something, the swarms does it better; by adaptation of greedy selection and random search. The ABC algorithm simulates the foraging behavior of honey bees. The local search in two stages in each step and global search are responsible for making this algorithm a robust search technique. The details of this algorithm are discussed here. Because of its very strong search process, computational simplicity and ease of modification according to the problem, the ABC algorithm is now finding more widespread applications in business, scientific and engineering circles. In this paper, we provide a thorough and extensive overview of most research work focusing on the application of ABC, with the expectation that it would serve as a reference material to both old and new, incoming researchers to the field, to support their understanding of current trends and assist their future research prospects and directions. Also new proposed architecture of Enhanced ABC algorithm for image ranking is also given here.

Other Details

Paper ID: IJSRDV1I9019
Published in: Volume : 1, Issue : 9
Publication Date: 01/12/2013
Page(s): 1767-1771

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