Solving shortest path problem using particle swarm optimization

This paper presents the investigations on the application of particle swarm optimization (PSO) to solve shortest path (SP) routing problems. A modified priority-based encoding incorporating a heuristic operator for reducing the possibility of loop-formation in the path construction process is propos...

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Main Authors: Mohemmed, Ammar W., Sahoo, Nirod Chandra, Tan, Kim Geok
Format: Article
Published: Elsevier 2008
Subjects:
Online Access:http://shdl.mmu.edu.my/2271/
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author Mohemmed, Ammar W.
Sahoo, Nirod Chandra
Tan, Kim Geok
author_facet Mohemmed, Ammar W.
Sahoo, Nirod Chandra
Tan, Kim Geok
author_sort Mohemmed, Ammar W.
building MMU Institutional Repository
collection Online Access
description This paper presents the investigations on the application of particle swarm optimization (PSO) to solve shortest path (SP) routing problems. A modified priority-based encoding incorporating a heuristic operator for reducing the possibility of loop-formation in the path construction process is proposed for particle representation in PSO. Simulation experiments have been carried out on different network topologies for networks consisting of 15-70 nodes. It is noted that the proposed PSO-based approach can find the optimal path with good success rates and also can find closer sub-optimal paths with high certainty for all the tested networks. It is observed that the performance of the proposed algorithm surpasses those of recently reported genetic algorithm based approaches for this problem. (c) 2008 Elsevier B.V. All rights reserved.
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spelling mmu-22712020-12-21T07:32:52Z http://shdl.mmu.edu.my/2271/ Solving shortest path problem using particle swarm optimization Mohemmed, Ammar W. Sahoo, Nirod Chandra Tan, Kim Geok T Technology (General) QA75.5-76.95 Electronic computers. Computer science This paper presents the investigations on the application of particle swarm optimization (PSO) to solve shortest path (SP) routing problems. A modified priority-based encoding incorporating a heuristic operator for reducing the possibility of loop-formation in the path construction process is proposed for particle representation in PSO. Simulation experiments have been carried out on different network topologies for networks consisting of 15-70 nodes. It is noted that the proposed PSO-based approach can find the optimal path with good success rates and also can find closer sub-optimal paths with high certainty for all the tested networks. It is observed that the performance of the proposed algorithm surpasses those of recently reported genetic algorithm based approaches for this problem. (c) 2008 Elsevier B.V. All rights reserved. Elsevier 2008-09 Article NonPeerReviewed Mohemmed, Ammar W. and Sahoo, Nirod Chandra and Tan, Kim Geok (2008) Solving shortest path problem using particle swarm optimization. Applied Soft Computing, 8 (4). pp. 1643-1653. ISSN 1568-4946 http://dx.doi.org/10.1016/j.asoc.2008.01.002 doi:10.1016/j.asoc.2008.01.002 doi:10.1016/j.asoc.2008.01.002
spellingShingle T Technology (General)
QA75.5-76.95 Electronic computers. Computer science
Mohemmed, Ammar W.
Sahoo, Nirod Chandra
Tan, Kim Geok
Solving shortest path problem using particle swarm optimization
title Solving shortest path problem using particle swarm optimization
title_full Solving shortest path problem using particle swarm optimization
title_fullStr Solving shortest path problem using particle swarm optimization
title_full_unstemmed Solving shortest path problem using particle swarm optimization
title_short Solving shortest path problem using particle swarm optimization
title_sort solving shortest path problem using particle swarm optimization
topic T Technology (General)
QA75.5-76.95 Electronic computers. Computer science
url http://shdl.mmu.edu.my/2271/
http://shdl.mmu.edu.my/2271/
http://shdl.mmu.edu.my/2271/