组合优化策略的改进协同优化方法
Improved collaborative optimization based on hybrid optimization strategy

为克服传统协同优化方法一致性约束造成的收敛困难和局部最优问题，提出将粒子群优化算法和修正可行方向法结合并引入协同优化. 应用粒子群算法获得全局最优解近似，在此基础上应用修正可行方向法进行局部精确搜索. 分别以一个典型的二次函数优化问题和一个减速器设计优化问题作为测试实例，优化结果表明，所提出组合优化策略是有效的，同时兼顾了优化效率和精度.
To solve the problems of poor convergence and local optimization in standard collaborative optimization (CO) due to the consistency constraints，particle swarm optimization (PSO) and modified method of feasible direction (MMFD) were proposed into the framework of CO. PSO was first employed to approximate the globally optimal solution. Subsequently，MMFD was applied to calculate the globally optimal solution accurately. Using the improved CO，two representative examples were examined. One illustrated the optimization of a quadratic function，the other concerned the design optimization of a reducer. Optimization results demonstrated the validity of the proposed hybrid optimization strategy，and improve the efficiency and accuracy of optimization as well