Paper and pulp industry is facing a lot of challenges in recent years basically due to the increase in use of digital technologies, which has lessened the demand of some papers product, and also because of the everyday augmenting pressure of the markets. Stora Enso, nowadays, is one of the biggest pulp and paper manufacturers and if it wants to keep on being competent the right strategies need to be taken. This Thesis presents the Strategic Network Planning (SNP) for Stora Enso, which is a planning strategy with the longest horizon. This planning tool sets the long term planning stratagem the company has to take. Typically it includes decisions on which plants to build, scale up, scale down or close in the earlier part of the planning period, such as 1-3 years. However, in order to make such decisions, a longer time horizon needs to be considered. In this Thesis it has been built an optimization model, more specifically, a Mixed Integer Problem (MIP). To accomplish that, it has been necessary to obtain the data concerning the SNP for the company in the next 10 years. Using this optimization tool has proved great saving for the companies using them and due to the more and tighter economic margins its use is increasing every day. For getting results it will be used AMPL, an algebraic modeling language for optimization problems. The solver used will be CPLEX. The solutions obtained after running the program will be a tool for aiding in decisions rather than being the final answers on how the company structure will be set up, since non-quantitative aspects and non-modeled expertise and experience also play an important role. Due to the big number of results in this kind of planning problems, solution considered of essential importance to the reader would be presented in the paper. However, the reader should be aware that there are some files enclosed with the Thesis where anyone interested can find the rest of results. This will be found in the registers of the Industrial Engineering University called ETSEIB (UPC) of Barcelona, Spain.

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