A genetic algorithm to solve the robust design problem for a Flow Network with Node Failure

The robust design problem in a flow network is defined as search optimal node capacity that can be assigned such that the network still survived even under the node’s failure. This problem is considered as an NP-hard. So, this paper proposes a genetic algorithm-based approach to solve it for a flow network with node failure. The proposed based genetic approach is used to assign the optimal capacity for each node to minimize the total capacities and maximize the network reliability. The proposed approach takes the capacity for each critical node should have the maximum capacity (usually equals to the demand value) to alleviate that the reliability to drop to zero. Three network examples are used to show the efficiency of our algorithm. Also, the results obtained by our approach are compared with those obtained by the previous approximate algorithm.