Abstract
Network design decisions in strategic communication networks have attracted widespread interest from the scientific community in the last decades. Since real-world cases are complex and computationally challenging systems that require effective optimization techniques, therefore recently, approximate resolution methods, specifically metaheuristics frameworks are in focus. In this research, we investigate a specific variant of Network Design Problems (NDPs), namely the Generalized Discrete Cost Multicommodity Network Design Problem (GDCMNDP), which seeks to find a network that optimizes the total costs while fulfilling several design restrictions. A promising newly developed solution approach based on the Archimedes Optimization Algorithm (AOA) that has not been tackled in the previous studies for solving NDPs is proposed. To assess its performance, the proposed approach is applied to benchmark network scenarios from the literature. The obtained solutions are compared with well-known state-of-the-art metaheuristic solutions. Results highlight the promising performance of the AOA for solving such NP-hard Network Design Problems.
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Mejri, I., Layeb, S.B., Koussani, J. (2023). Solving a Generalized Network Design Problem Using the Archimedes Optimization Algorithm. In: Vasant, P., Weber, GW., Marmolejo-Saucedo, J.A., Munapo, E., Thomas, J.J. (eds) Intelligent Computing & Optimization. ICO 2022. Lecture Notes in Networks and Systems, vol 569. Springer, Cham. https://doi.org/10.1007/978-3-031-19958-5_2
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