The Application of Simulated Annealing Algorithm in Forest Simulation Optimation System

Abstract

Given that forests comprise a large portion of the global land area, forestry management plays a significant role in ecological protection. The traditional method of advocating less deforestation is no longer suitable for the sustainable development of current socio-economic. In this paper, a multi-target analysis and planning model for the forest is proposed. The main aspects of evaluating a forest, including its social value, economic value and ecological value are taken into consideration. Subsequently, the penalty function is applied to simulated annealing algorithm, transforming the problem with constraints into an unconstrained problem. Thus an algorithm base that can search for the global optimal solution to the multi-objective problem, and obtain the best forestry management strategy for each kind of forest is proposed. Experiments have demonstrated encouraging results. Drawbacks such as the demand of strict restriction of the data, the occurrence of overfitting, and easy to be trapped in a local optimal solution are conquered in the proposed algorithm, which always appear in the traditional methods like linear programming, polynomial fitting and hill-climbing algorithm. It is resulted that the temperature decay factor greatly affects the efficiency of the iteration of the algorithm, and the choice of parameters is very important for the algorithm.