Camacho-Vallejo José-Fernando, Mar-Ortiz Julio, López-Ramos Francisco, Rodríguez Ricardo Pedraza
Universidad Autónoma de Nuevo León, Facultad de Ciencias Físico-Matemáticas, San Nicolás de los Garza, Nuevo León, México.
Universidad Autónoma de Tamaulipas, Facultad de Ingeniería, Tampico, Tamaulipas, México.
PLoS One. 2015 Jun 23;10(6):e0128067. doi: 10.1371/journal.pone.0128067. eCollection 2015.
Local access networks (LAN) are commonly used as communication infrastructures which meet the demand of a set of users in the local environment. Usually these networks consist of several LAN segments connected by bridges. The topological LAN design bi-level problem consists on assigning users to clusters and the union of clusters by bridges in order to obtain a minimum response time network with minimum connection cost. Therefore, the decision of optimally assigning users to clusters will be made by the leader and the follower will make the decision of connecting all the clusters while forming a spanning tree. In this paper, we propose a genetic algorithm for solving the bi-level topological design of a Local Access Network. Our solution method considers the Stackelberg equilibrium to solve the bi-level problem. The Stackelberg-Genetic algorithm procedure deals with the fact that the follower's problem cannot be optimally solved in a straightforward manner. The computational results obtained from two different sets of instances show that the performance of the developed algorithm is efficient and that it is more suitable for solving the bi-level problem than a previous Nash-Genetic approach.
本地接入网络（LAN）通常用作通信基础设施，以满足本地环境中一组用户的需求。通常，这些网络由通过网桥连接的几个LAN网段组成。拓扑LAN设计双层问题在于将用户分配到集群，并通过网桥将集群联合起来，以获得具有最小连接成本的最小响应时间网络。因此，领导者将做出将用户最优地分配到集群的决策，而跟随者将做出在形成生成树时连接所有集群的决策。在本文中，我们提出了一种遗传算法来解决本地接入网络的双层拓扑设计问题。我们的求解方法考虑了斯塔克尔伯格均衡来解决双层问题。斯塔克尔伯格-遗传算法程序处理了跟随者的问题不能以直接的方式得到最优解这一事实。从两组不同的实例获得的计算结果表明，所开发算法的性能是高效的，并且它比以前的纳什-遗传方法更适合解决双层问题。
