We consider the context of a telecommunications company that is at the same time an infrastructure operator and a service provider. When planning its network expansion, the company can leverage over its knowledge of subscribers dynamic to better optimize the network dimensioning, therefore avoiding unnecessary costs. In this work, the network expansion represents the deployment and/or reinforcement of several technologies (e.g. 2G,3G,4G), assuming that subscribers to a given technology can be served by this technology or older ones. The operator can influence subscribers dynamic by subsidies. The planning is made over a discretized time horizon while some strategic guidelines requirements are demanded at the end of the time horizon. Following classical models, we consider that the behavior of customers follows an S-shape piecewise constant function. We propose a Mixed-Integer Linear Programming formulation and a heuristic algorithm for the multi-year planning problem. The scalability of the formulation and the quality of the heuristic are assessed numerically on real instances for a use-case with two generations
