Abstract
In this paper, we propose a mixed integer linear programming (MILP) model for a telecommunication highway vehicle network to optimally locate roadside units (RSUs) at minimum costs. Our model is quite general and thus can be used in highway networks where emerging technologies related with Massive Multiple Input Multiple Output (MIMO) systems can be implemented. For this purpose, let graph G(V,E) represent a highway vehicle network with sets V and E denoting RSUs and connection links between them, respectively. The optimization problem consists of finding a subset of RSUs from V that satisfies a coverage vehicle flow and Hamiltonian backbone network constraints while spanning the highway at minimum cost. Then, we further propose an iterative greedy heuristic and a local search algorithm which allow feasible solutions to be obtained in significantly less CPU time than CPLEX solver requires to solve the MILP model. Preliminary numerical results indicate that our proposed model is able to solve network instances with up to 1500 RSUs to optimality in less than one hour. Whilst the proposed heuristic and local search algorithms allow to obtain near optimal solutions with gap values which are lower than 6% and 1%, respectively for most tested instances.
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