In large-scale computer communication networks (e.g. the nowadays Internet), the assignment of link capacity and the selection of routes are extremely complex network optimization problems. Efficient solutions to these problems are much sought after because such solutions could lead to considerable monetary savings and better utilization of the networks. Unfortunately, as indicated by much prior theoretical research, these problems belong to the class of nonlinear combinatorial optimization problems, which are mostly (if not all) NP-hard problems. Metaheuristics, such as genetic and simulated annealing algorithms, are widely applicable heuristic optimization strategies that have shown encouraging results for a large number of difficult combinatorial optimization problems. In this paper, we propose three different approaches for solving the routing and capacity assignment (RCA) problem. The first approach uses a GA. The second approach uses the SA algorithm. The last approach combines the GA with the SA to improve the performance of the GA. The paper also presents the experiments that we have conducted to evaluate the effectiveness of the proposed approaches compared to a one of the heuristic algorithms for solving the same problem. The results show that the hybrid approach is more efficient in finding good solutions to the RCA problem compared to other techniques.
R. Girgis, et al, M.
"Routing and Capacity Assignment Problem in Computer Networks Using Genetic Algorithm,"
Information Sciences Letters: Vol. 2
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Available at: https://digitalcommons.aaru.edu.jo/isl/vol2/iss1/3