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An Alternative Genetic Algorithm to Optimize OSPF Weights

In this paper, a method based on genetic algorithm (GA), is presented to optimize administrative weights for OSPF routing. This method can be seen as an alternative to the local-search method in [1] or another GA-based method in [11]. However, the GA as well as the objective function we use are different. Instead of minimizing a convex cost function we prefer to minimize the maximum and average utilization directly. This objective function is similar as one proposed in [7, 8]. In addition we implement a method to search weights for both single and multiple shortest paths routing and propose an enhancement to the objective function to minimize weight changes for an existing operational network. We will demonstrate our method in a case of small networks and compare the results with MIP-based (Mixed Integer Programming) method from [7, 8, 10]. Afterwards we will show the results for a bigger network with increasing traffic demands, compared with the results of some conventional weight settings as well as with the lower bound of general optimal routing (linear program / LP solution).