<?xml version="1.0" encoding="UTF-8"?> <article key="pdf/14013" mdate="2009-04-28 00:00:00"> <author>Sandeep Singh Gill and Rajeevan Chandel and Ashwani Chandel</author> <title>Comparative Study of Ant Colony and Genetic Algorithms for VLSI Circuit Partitioning</title> <pages>1149 - 1153</pages> <year>2009</year> <volume>3</volume> <number>4</number> <journal>International Journal of Electrical and Computer Engineering</journal> <ee>https://publications.waset.org/pdf/14013</ee> <url>https://publications.waset.org/vol/28</url> <publisher>World Academy of Science, Engineering and Technology</publisher> <abstract>This paper presents a comparative study of Ant Colony and Genetic Algorithms for VLSI circuit bipartitioning. Ant colony optimization is an optimization method based on behaviour of social insects 27 whereas Genetic algorithm is an evolutionary optimization technique based on Darwinian Theory of natural evolution and its concept of survival of the fittest 19. Both the methods are stochastic in nature and have been successfully applied to solve many Non Polynomial hard problems. Results obtained show that Genetic algorithms out perform Ant Colony optimization technique when tested on the VLSI circuit bipartitioning problem. </abstract> <index>Open Science Index 28, 2009</index> </article>