基于随机多属性决策的红松人工林适应性经营优化

适应性经营优化是近年来森林经营决策的一种新技术，利用随机模拟与确定性模型相结合的方法，量化森林经营过程中的不确定性因素，有效实现森林的适应性经营管理，为研究与探索“不确定性对森林经营”的影响提供了独到的方法和途径。本研究以东北红松人工林为例，利用时间序列模型、随机游走模型和气候情景相结合的方法，构建林木生长、松塔产量和立木价格随机模拟模型，并整合单木生长模型建立林分情景模拟器用于推演林分动态；基于适应性经营理论分析林分未来情景与经营决策变量之间的关系，提出保留价格函数和数量经营指导模型；根据随机多属性决策和随机多目标可接受分析法建立林分多目标经营决策模型，同时确定各目标间的权衡关系并利用群体算法优化求解；在此基础上探究预期优化与适应性优化的差异，提出不同经营目标、不同林分条件下的适应性经营模式，从而有效提高红松人工林多目标经营水平。

Adaptive management optimization is a recent state-of-the-art approach for supporting decision making in forest management and planning. It combines stochastic simulations with deterministic models to quantify the uncertainty of factors influencing forest management. The optimized outcomes provide the best options for forest management to adapt to the constantly changing and often challenging situations. This proposed study intends to take the Korean pine plantations in Northeast China as an example. Time series analyses and random walk methods together with climate scenarios are utilized to develop stochastic models of tree growth, cone yield and timber prices. Stochastic models and individual-tree models are combined together to formulate a stand-level scenario simulator that produces different scenarios for the future development of the stand. Based on the theory of adaptive optimization, reservation price and quantify functions are developed to serve as instructions in optimal adaptive management. Multi-objective management decision model is established by the method of stochastic multi-attribute decision and stochastic multi-objective acceptability analysis which determine the trade-off among the objectives. Population-based algorithms are used to optimize the parameters of the adaptive rules. Management strategies based on decision rules for adaptive multi-objective management will be compared to the results of stochastic anticipatory optimization and deterministic optimization. Optimization results for alternative management objectives are used to develop instructions for the adaptive management of different types of Korean pine forests over a range of site conditions. The use of these instructions will improve the efficiency of multi-objective management of Korean pine plantations.