Research Article
Extended Ant Colony Optimization Algorithm (EACO) for Efficient Design of Networks and Improved Reliability
@INPROCEEDINGS{10.1007/978-3-642-37949-9_81, author={Mohd Ashraf and Rajesh Mishra}, title={Extended Ant Colony Optimization Algorithm (EACO) for Efficient Design of Networks and Improved Reliability}, proceedings={Quality, Reliability, Security and Robustness in Heterogeneous Networks. 9th International Conference, QShine 2013, Greader Noida, India, January 11-12, 2013, Revised Selected Papers}, proceedings_a={QSHINE}, year={2013}, month={7}, keywords={ACO Network Reliability Optimization Heuristic Topology}, doi={10.1007/978-3-642-37949-9_81} }- Mohd Ashraf
Rajesh Mishra
Year: 2013
Extended Ant Colony Optimization Algorithm (EACO) for Efficient Design of Networks and Improved Reliability
QSHINE
Springer
DOI: 10.1007/978-3-642-37949-9_81
Abstract
The problem of efficient network design is nothing but the NP hard problem which consisting of possible links subset selection or network topology to lower network cost subjected to the reliability constraint. Thus, in this paper we are presenting the new improved method of ant colony optimization in order to overcome such network design problem. This new algorithm is based on existing ant colony optimization algorithm. This new algorithm is having aim to optimize network reliability with least cost. This new proposed algorithm we called as extended ant colony optimizations (EACO) in which two new methods are presented, those two methods are used to optimize the search process for neighborhood and re-initialization process. Here we presented the practical approach with different network topologies in order to show the efficiency of proposed algorithm. The results of proposed method are compared with previous existing algorithms such as tabu search algorithm (TSA), genetic algorithm (GA), and ACO. From the simulation results, the proposed approach is better reliability as compared to existing algorithms.