Optymalizacja przewozów drewna nabywanego w jednostkach Lasów Państwowych

Since many years much attention has been paid to the rationality of wood transportation criteria due to the realization of social objectives. Identification and elimination of unnecessary haulage can reduce the total cost of transport and contribute to reducing fuel consumption, carbon dioxide emissions and accident risk. This paper concerns decision support for the allocation of available wood as a lot of irrationality of the existing wood transport operations has been observed. The aim of the study was to develop and test the method of optimizing the allocation of wood available in forest districts for selected groups of customers from over the country, taking into account the criterion of export distance (geography of purchase). The scale of the effects of applying the proposed optimization method is also presented. Data on sales of medium size S2A Scots pine wood in 2015 was used. A model of a two−dimensional transport task was built in order to optimize wood allocation. The road distance between the points where the wood was loaded and the points where it is processed was determined using the transportation network and network analysis performed in ArcGIS software. Linear programming was used to develop a software to support the allocation of wood to a group of selected customers nationwide. It was assumed that the benefits of optimization would be shared by whole group and not just by each customer individually. Changing existing supply locations can significantly shorten the average transportation distances up to 31% for particular customers (tab. 2), while for the whole group of analysed customers the reduction amounted to 14%. As a result of the proposed method, the transportation work would be reduced by 65 mio m3, which would reduce the average distance of timber exports by 15 km. This allows shortening of over 174 thousand of truckloads. The savings from the shortage of truck− loads will amount to over 1.1 mio l of diesel fuel, which is worth about 5 mio PLN (1.18 mio ).