@Article{cmc.2020.010881,
AUTHOR = {Ahmed Y. Hamed, Monagi H. Alkinani, M. R. Hassan},
TITLE = {A Genetic Algorithm to Solve Capacity Assignment Problem in a  Flow Network},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {64},
YEAR = {2020},
NUMBER = {3},
PAGES = {1579--1586},
URL = {http://www.techscience.com/cmc/v64n3/39445},
ISSN = {1546-2226},
ABSTRACT = {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.},
DOI = {10.32604/cmc.2020.010881}
}