A Genetic Algorithm to Solve Capacity Assignment Problem in a Flow Network

Computer networks and power transmission networks are treated as capacitated flow networks. A capacitated flow network may partially fail due to maintenance. Therefore, the capacity of each edge should be optimally assigned to face critical situations—i.e., to keep the network functioning normally i...

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Bibliographic Details
Published in:Computers, materials & continua materials & continua, 2020-01, Vol.64 (3), p.1579-1586
Main Authors: Hamed, Ahmed Y, Alkinani, Monagi H, Hassan, M R
Format: Article
Language:English
Subjects:
Computer networks
Genetic algorithms
Network computers
Operations research
Optimization
Robust design
System reliability
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Summary:Computer networks and power transmission networks are treated as capacitated flow networks. A capacitated flow network may partially fail due to maintenance. Therefore, the capacity of each edge should be optimally assigned to face critical situations—i.e., to keep the network functioning normally in the case of failure at one or more edges. The robust design problem (RDP) in a capacitated flow network is to search for the minimum capacity assignment of each edge such that the network still survived even under the edge’s failure. The RDP is known as NP-hard. Thus, capacity assignment problem subject to system reliability and total capacity constraints is studied in this paper. The problem is formulated mathematically, and a genetic algorithm is proposed to determine the optimal solution. The optimal solution found by the proposed algorithm is characterized by maximum reliability and minimum total capacity. Some numerical examples are presented to illustrate the efficiency of the proposed approach.
ISSN:1546-2226
1546-2218
1546-2226
DOI:10.32604/cmc.2020.010881