OPTIMIZATION MODEL OF SELECTIVE CUTTING FOR TIMBER HARVEST PLANNING BASED ON A SIMULATED ANNEALING APPROACH

Abstract

An optimization model for Timber Harvest Planning (THP) is used to form harvest areas with the objective of maximizing the tree harvest volume subject to harvest regulations. Most optimization models for THP currently in use are based on clear cutting and restricted to adjacency constraints to prevent the creation of large clear-cut openings in the forest. However, an optimization model based on selective cutting-the cutting technique utilized in tropical countries-has rarely been described in the literature. The aim of this study was to propose an optimization model for THP based on selective cutting and subject to a maximum number of trees to be harvested and a minimum number of trees to be damaged during each planning period. The model was solved using three optimization techniques to identify the most suitable technique for use in the process of harvest area formation: Monte Carlo Programming (MCP), Simulated Annealing (SA) and Threshold Acceptance (TA). The obtained results indicate that the SA method provides better solutions than the MCP and TA methods, regardless of problem size. As a conclusion, the proposed model provides a tool to generate timber harvest plans with the improved monitoring and control techniques used in harvesting operations in tropical countries.