Research on the application of search algorithm in computer communication network
Abstract: This article mitigates the challenges of previously reported literature by reducing the operating cost and improving the performance of network. A genetic algorithm-based tabu search methodology is proposed to solve the link capacity and traffic allocation (CFA) problem in a computer communication network. An efficient modern super-heuristic search method is used to influence the fixed cost, delay cost, and variable cost of a link on the total operating cost in the computer communication network are discussed. The article analyses a large number of computer simulation results to verify the effectiveness of the tabu search algorithm for CFA problems and also improves the quality of solutions significantly compared with traditional Lagrange relaxation and subgradient optimization algorithms. The experimental results show that with the increase of the weighted coefficient of variable cost, the proportion of variable cost in the total cost increases from 10 to 35%. The growth is relatively slow, and the fixed cost is still the main component. In addition, due to the increase in the variable cost, the tabu search algorithm will also choose the link with large luxury to reduce the variable cost, which makes the fixed cost slightly increase, while the network delay cost and average delay slightly decrease. The proposed method, when compared with the genetic algorithm, has more advantages for large-scale or heavy-load networks.
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Language
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Englisch
- Bibliographic citation
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Research on the application of search algorithm in computer communication network ; volume:31 ; number:1 ; year:2022 ; pages:1150-1159 ; extent:10
Journal of intelligent systems ; 31, Heft 1 (2022), 1150-1159 (gesamt 10)
- Creator
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Ai, Hua
Chai, Jianwei
Zhang, Jilei
Khanna, Shaweta
Ghafoor, Kayhan Zrar
- DOI
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10.1515/jisys-2021-0263
- URN
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urn:nbn:de:101:1-2022110113082280095960
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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15.08.2025, 7:25 AM CEST
Data provider
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Ai, Hua
- Chai, Jianwei
- Zhang, Jilei
- Khanna, Shaweta
- Ghafoor, Kayhan Zrar
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