模拟和优化是林分水平森林经营和规划过程中最直接有效的现代技术手段。然而，针对当今森林多目标（经济和生态）经营问题，我国缺乏利用优化及决策技术分析不同立地条件和林分密度下的最优经营方案，实现森林经营目标。因此，本项目以东北红松人工林长期调查数据及建立的生长模型为基础，利用林分生长与收获模拟器模拟不同经营措施对红松人工林木材产量、松籽产量和碳储量的影响；基于多属性效用理论和惩罚函数构建红松人工林多目标经营规划模型；采用Hooke&Jeeves算法对群体算法（微分进化和粒子群优化算法）的参数进行优化，实现所用算法在最优参数配置下的优化求解；分析最优经营措施对不同经营目标的影响，构建林分优化经营模式，从而有效的开展红松人工林的多功能优化经营。

Forest management and planning at the stand level uses efficient and modern techniques based on simulation and optimization. However, for the achievement of forest management objectives with optimal management scenario based on different site conditions and stand densities, practical experience on management optimization and other decision-making techniques is limited in China for current forest multi-objective management (including economic and ecological benefits). Based on the long-term growth data of Korean pine plantation of northeastern China and yield models that have already been developed, this proposal will establish a forest growth and harvest stimulator which predicts timber production, Korean pine nuts production, and carbon storage in alternative management schedules. The combination of multi-attribute utility theory and penalty function is used to develop the multi-objective management and planning models for the Korean pine plantation. The parameters of differential evolution and particle swarm optimization which belong to population-based algorithm are optimized based on Hooke & Jeeves algorithm. The best population-based algorithm is selected to optimize the management of Korean pine plantation and analyze the trade-offs among different management objectives. The optimization results for different management objectives are used to develop stand management mode to achieve the multi-functional management of Korean pine plantation.