Nowadays, changeable economic conditions and supply chain dynamics are obliging manufacturing and distribution companies to turn to network design as a solution to remain relevant in the global marketplace. Factors such as wide variety of products, global markets, and more demanding customers, among others, are making companies to deal with more and more complex supply chain networks. A large strand of research has been devoted to supply chain networks (see, e.g., [1] and references therein). This research extends the work in the field of logistic network design problems by introducing a new mixed integer linear programming model that includes some extra constraints. Additionally to location choices for plants and warehouses with supplier and transportation modes, product range assignment and product flows, this model incorporates modular capacity choices for plants and warehouses, minimum levels of service and non full coverage of customer demands. The non full coverage allows to model situations on which organizations can opt for outsourcing. Nowadays, many public and private organizations are using outsourcing as a way to improve their effectiveness and efficiency [2]. Despite being commonly related with services, outsourcing can be used as an alternative way for the company production, as well. To the best of our knowledge, supply chain network models with non mandatory full coverage demands have never been considered in the literature. Computational experiments on different data sets are presented and the corresponding solutions are discussed. REFERENCES [1] Johnston, R., Clark, R. (2008). Service operations Management - Improving service delivery, Prenctice Hall. [2] Mula, J., Peidro, D., Díaz-Mandronero, M., Vicens E. (2011). Mathematical programming models for supply chain production and transport planning. European Journal of Operational Research 204, 377-390.

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Logistics, Network Design, Mixed Integer Linear Programming