Applying dynamic multiple-objective optimization in inter-enterprise collaboration to improve the efficiency of energy wood transportation and storage - Palander, Teijo (Scandinavian journal of forest research, 2015)
In Finland, VR Group (the state-owned railway company) provides third-party logistics services (3PLs) for industrial customers. Their current static, single-objective optimization model does not support inter-enterprise collaboration to achieve optimal railway logistics. In this study, I introduce a collaborative decision-support method that can be applied to manage railway traffic under a scenario of increasing imports of Russian wood. Based on the data obtained to support this research, I describe railway traffic strategy scenarios in terms of 3PLs to account for the changed energy wood transportation and storage needs related to imported Russian wood. In the scenarios, the railway wagon rotation was adjusted to reach a globally optimal strategy that achieves efficient wood procurement logistics for the Finnish forest industry. These decisions were based on a comprehensive logistics analysis of the integrated wood demand and a supply chain model for southeastern Finland in the context of collaborative decision-making among members of the logistics chain. The model, which is based on dynamic multiple-objective linear programming, supports inter-enterprise collaboration because the adaptation of Russian wood imports to the regional railway transportation environment will require continuous, integrated optimization of the flows of wood and railway wagons.