Genetic Algorithm-based Study on Flow Allocation in a Multicommodity Stochastic-flow Network with Unreliable Nodes
Qiang Liu, Hailin Zhang, Xiaoxian Ma, Zhao Qing-zhen · 2007
Many real-life networks can be abstracted into a stochastic-flow network. In this paper, we assume there are several sorts of resource flows transmitting through a stochastic-flow network with unreliable nodes. We want to find a optimal resource flow allocation and control strategy upon arcs and nodes. Under this strategy, the probability of satisfying sink nodes' demand is maximized when resource flows transmit from source nodes to sink nodes. We propose a genetic algorithm to seek the optimal strategy. At last, a numerical example is given to test the proposed algorithm.