The paper consists of a report of a study tour made by Finnish forestry students, under the leadership of the author, to Harbin, Changchun, Peking, Nanking and Shanghai in December 1977. In addition, some earlier literature sources concerning forestry in China are briefly reviewed. The paper presents the general geographic characteristics of north-eastern China, as well as the vegetation zones and timber species of this region. Silvicultural methods and the main features of forest technology and forest industry are also discussed. The last chapters describe the forestry administration and current trends in forestry education and research in north-eastern China as observed during the tour.
The PDF includes a summary in Finnish.
This review systematically analyses and classifies research and review papers focusing on discrete event simulation applied to wood transport, and therefore illustrates the development of the research area from 1997 until 2017. Discrete event simulation allows complex supply chain models to be mapped in a straightforward manner to study supply chain dynamics, test alternative strategies, communicate findings and facilitate understanding of various stakeholders. The presented analyses confirm that discrete event simulation is well-suited for analyzing interconnected wood supply chain transportation issues on an operational and tactical level. Transport is the connective link between interrelated system components of the forest products industry. Therefore, a survey on transport logistics allows to analyze the significance of entire supply chain management considerations to improve the overall performance and not only one part in isolation. Thus far, research focuses mainly on biomass, unimodal truck transport and terminal operations. Common shortcomings identified include rough explanations of simulation models and sparse details provided about the verification and validation processes. Research gaps exist concerning simulations of entire, resilient and multimodal wood supply chains as well as supply and demand risks. Further studies should expand upon the few initial attempts to combine various simulation methods with optimization.