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A Hybrid Ant Colony Optimization Algorithm for Network Routing and Planning

by Mahendra Pratap Panigrahy, Paramjeet Kaur
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 72 - Number 15
Year of Publication: 2013
Authors: Mahendra Pratap Panigrahy, Paramjeet Kaur
10.5120/12570-8958

Mahendra Pratap Panigrahy, Paramjeet Kaur . A Hybrid Ant Colony Optimization Algorithm for Network Routing and Planning. International Journal of Computer Applications. 72, 15 ( June 2013), 15-19. DOI=10.5120/12570-8958

@article{ 10.5120/12570-8958,
author = { Mahendra Pratap Panigrahy, Paramjeet Kaur },
title = { A Hybrid Ant Colony Optimization Algorithm for Network Routing and Planning },
journal = { International Journal of Computer Applications },
issue_date = { June 2013 },
volume = { 72 },
number = { 15 },
month = { June },
year = { 2013 },
issn = { 0975-8887 },
pages = { 15-19 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume72/number15/12570-8958/ },
doi = { 10.5120/12570-8958 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:38:00.301510+05:30
%A Mahendra Pratap Panigrahy
%A Paramjeet Kaur
%T A Hybrid Ant Colony Optimization Algorithm for Network Routing and Planning
%J International Journal of Computer Applications
%@ 0975-8887
%V 72
%N 15
%P 15-19
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The mechanism of route search problem is applied to various engineering fields. The various researches for the dynamic routing only revile the shortest path from source to destination but not vice versa. Ant colony optimization (ACO) algorithms have proved to be able to adapt to dynamic optimization problems (DOPs) when stagnation behavior is avoided. Several approaches have been integrated with ACO to improve its performance for DOPs. The main objective of this work is to search out the least-time-cost route in a variable-edge-weight graph. It can find multiple transmission paths from sources to the goal by parallel search. We introduce time-dependent pheromones and feedback path model as two heuristic factors to improve the basic ACO. Finally, this proposed heuristic algorithm is verified to be steady-going by repeated testing [1]. Ant Colony Optimization Technique has been applied in different network models with different number of nodes and structure to find the shortest path with optimum throughput. The simulation results show that the proposed dynamic ACO algorithm can effectively reduce time cost by avoiding the dynamic congestion areas. The experimental results show that the algorithm is more effective than the existing ones and it improves the Quality of Service (QoS) [13[14][15].

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Index Terms

Computer Science
Information Sciences

Keywords

NP-Complete ACO DOPs Time-Dependent Pheromones Feedback Path Model Dynamic Congestion Areas

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