ABSTRACT The aim of this study was to develop a mathematical model for the spatial forest planning of harvest activity scheduling. Thirty-eight (38) blocks were formed from stands aged 13 to 17 years considering a total area limit set to 350 hectares. The model was built in Excel ® spreadsheet and solved by CPLEX® optimization software using the Branch and bound method for the linear programming of problems with integer variables. The results of optimization are presented in the form of a map of spatial distribution of the selected blocks. The total harvested area was 5,989 hectares and the volume generated was 2,956,913 m3 in a planning horizon of five years. Higher results compared with those of traditional planning and efficiency to optimize forest harvesting proved to be a viable alternative to the inclusion of space and operational issues associated with forest harvesting.

ABSTRACT: The application of optimization methods to forest management has given rise to a successful line of investigation in recent decades. However, there have been few publications associated with the application of these techniques to the management of industrial forest plantations (those with short or medium rotations, always less than 50 years), which consider the important role played by these forest systems in the supply of diverse goods and services. This study presents an overview of this literature which, by analyzing 67 articles published in journals contained in the ISI Web of Science, highlight, among other aspects, the techniques employed, their evolution, their planning type (strategic, tactical or operational), the functional objectives and constraints considered, or the type of software deployed in these studies. The results show how Model I has been the one most frequently used in these studies, and how the spatial component is increasing in importance. However, classic optimization methods, such as mixed integer programming, have been those most commonly resorted to, although the employment of multi-criteria techniques such as goal programming and analytic hierarchical process have strongly emerged in recent years.