TY - GEN
T1 - Active GA Accelerated by Simulated Annealing to Solve SPP in Packet Networks
AU - Fonseca, Daniel S.
AU - Wanner, Elizabeth F.
AU - Marcelino, Carolina G.
AU - Silva, Gabriel P.
AU - Jimenez-Fernandez, Silvia
AU - Salcedo-Sanz, Sancho
PY - 2023/1/1
Y1 - 2023/1/1
N2 - This paper presents two approaches to deal with the shortest path problem (SPP) solution for routing network packets in an optimized way. The first one uses Simulated Annealing (SA), and the second one is a novel hybridization of the Genetic Algorithm with Dijkstra mutation accelerated by the SA (SGA). Also, two different case scenario configurations, each with 144 nodes, are employed to assess these two proposals, and the total time spent to fill out the routing tables, referring to the transmission of a packet from the initial to the destiny nodes, is measured. A statistical comparison is applied to identify differences among the algorithm’s solutions. Experiments and simulations have shown that the SGA presented competitive results compared to standard SA and can solve the problem with fast convergence, which makes us conclude that it can operate efficiently in actual computer networks.
AB - This paper presents two approaches to deal with the shortest path problem (SPP) solution for routing network packets in an optimized way. The first one uses Simulated Annealing (SA), and the second one is a novel hybridization of the Genetic Algorithm with Dijkstra mutation accelerated by the SA (SGA). Also, two different case scenario configurations, each with 144 nodes, are employed to assess these two proposals, and the total time spent to fill out the routing tables, referring to the transmission of a packet from the initial to the destiny nodes, is measured. A statistical comparison is applied to identify differences among the algorithm’s solutions. Experiments and simulations have shown that the SGA presented competitive results compared to standard SA and can solve the problem with fast convergence, which makes us conclude that it can operate efficiently in actual computer networks.
KW - Evolutionary algorithms
KW - Optimization
KW - Shortest path problem
UR - https://link.springer.com/chapter/10.1007/978-3-031-23236-7_24
UR - http://www.scopus.com/inward/record.url?scp=85147994607&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-23236-7_24
DO - 10.1007/978-3-031-23236-7_24
M3 - Conference publication
AN - SCOPUS:85147994607
SN - 9783031232350
T3 - Communications in Computer and Information Science
SP - 342
EP - 356
BT - Optimization, Learning Algorithms and Applications - Second International Conference, OL2A 2022, Proceedings
A2 - Pereira, Ana I.
A2 - Košir, Andrej
A2 - Fernandes, Florbela P.
A2 - Pacheco, Maria F.
A2 - Teixeira, João P.
A2 - Lopes, Rui P.
PB - Springer
T2 - 2nd International Conference on Optimization, Learning Algorithms and Applications, OL2A 2022
Y2 - 24 October 2022 through 25 October 2022
ER -