A Decision Support System for Multi-Criteria Forest Estate Planning, Integrating a Forest Growth Simulator, Fuzzy-Inference Techniques and a Heuristic Optimisation Approach

Abstract

The extended perception of sustainable forest development (MCPFE 2000) demands the integration of multiple management functions and criteria into strategic forest enterprise planning and decision making. Decision support systems (DSS) with effective model and method components can effectively support this planning procedure. For this, DSS must integrate tree growth simulators in order to run scenario simulations of stand dynamics, to project the long-term consequences of management alternatives and to scale stand dynamic processes at different spatial and temporal levels. Furthermore, DSS must include evaluation models capable of incorporating expert information and fuzzy reasoning. DSS should also integrate appropriate optimisation algorithms to identify optimal problem solutions dependent on multiple objectives. This chapter presents a DSS approach intended to support strategic multi-criteria forest planning and management at stand and estate levels. The DSS is aimed at forest enterprise managers as well as at the forest management planning services. Technically, the DSS integrates the individual tree-growth simulator SILVA 2.2 (Pretzsch 2001) and combines it with fuzzy-inference techniques and a heuristic Tabu Search optimisation approach. The main parts of the DSS concerning the technical structure, the database, the decision space, the objective system and the evaluation system will be presented as well as the main fuzzy-inference algorithms and utility functions. The heuristic multi-criteria optimisation approach developed for the specific DSS requirements will be shown. In addition, some example results demonstrating the DSS’s plausibility and sensitivity will be given. Finally, the chapter concludes with a brief discussion of the DSS approach and outlines perspectives for further research.