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Using heuristic algorithms for capacity leasing and task allocation issues in telecommunication networks under fuzzy quality of service constraints

机译:在服务质量模糊的情况下,使用启发式算法解决电信网络中的容量租赁和任务分配问题

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摘要

Nowadays, every firm uses telecommunication networks in different amounts and ways in order to complete their daily operations. In this article, we investigate an optimisation problem that a firm faces when acquiring network capacity from a market in which there exist several network providers offering different pricing and quality of service (QoS) schemes. The QoS level guaranteed by network providers and the minimum quality level of service, which is needed for accomplishing the operations are denoted as fuzzy numbers in order to handle the non-deterministic nature of the telecommunication network environment. Interestingly, the mathematical formulation of the aforementioned problem leads to the special case of a well-known two-dimensional bin packing problem, which is famous for its computational complexity. We propose two different heuristic solution procedures that have the capability of solving the resulting nonlinear mixed integer programming model with fuzzy constraints. In conclusion, the efficiency of each algorithm is tested in several test instances to demonstrate the applicability of the methodology.
机译:如今,每个公司都以不同的数量和方式使用电信网络来完成其日常运营。在本文中,我们调查了一家公司从一个市场中获取网络容量时面临的优化问题,在该市场中,存在多个提供不同定价和服务质量(QoS)方案的网络提供商。为了处理电信网络环境的不确定性,将由网络提供商保证的QoS级别和完成操作所需的最低服务质量级别表示为模糊数。有趣的是,上述问题的数学公式导致了众所周知的二维箱装箱问题的特殊情况,该问题以其计算复杂性而闻名。我们提出了两种不同的启发式求解程序,它们能够求解带有模糊约束的非线性混合整数规划模型。总之,在几个测试实例中测试了每种算法的效率,以证明该方法的适用性。

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