In this article, we focus on international facility location models. First, we conduct an extensive literature review on the subject and we propose a classification of the surveyed papers. The classification includes the modeling approach used, international factors, as well as dynamic and stochastic aspects of the approach. Based on the literature review, we find that international facility location problems received little attention. In particular, dynamic facility location models under uncertainty have been hardly studied. Therefore, we develop a stochastic dynamic international facility location model, using a Mixed-Integer Linear Programming (MILP) formulation. Through a case study, we show that international factors, as well as the dynamic and stochastic components of the problem, might influence strategic location decisions. We also quantify the added value of using a stochastic model instead of a deterministic counterpart and we derive insights regarding policies that governments can use to attract investments.
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Boujelben et al. (2017) studied this question.
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