A Hybrid GA and Tabu Search Approach to Find Optimal Node Placement in IP Networks

This paper covers the analyzing performance problems found in IP networks called Autonomous System (AS), to maximize the admitted traffic flows. We present a hybrid genetic algorithm approach to optimize the summary of admitted traffic where a hybrid GA approach is combined with an order-based Genetic Algorithm and Greedy then apply the Tabu Search Algorithm to find the optimal solution. We then, implement three certain algorithms to compare the results which are GA, K-center, and Greedy. In conclusion, the Tabu search algorithm shows the best performance and yielded significant improvements over techniques that only tried to minimize the length of the traffic routes or minimize bandwidth through the gateways.