Genetic Algorithm-based Study on Flow Allocation in a Multicommodity Stochastic-flow Network with Unreliable Nodes

Authors:
Qiang Liu;Hailin Zhang;Xiaoxian Ma;Qingzhen Zhao
Affiliations:
Shandong Normal University, China;Shandong Provincial Geo-mineral Engineering Exploration Institute, China;Shandong Normal University, China;Shandong Normal University, China
Venue:
SNPD '07 Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 01
Year:
2007

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Abstract

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.