基于蒙特卡洛的非线性约束条件下的优化算法研究

摘要

基于蒙特卡洛模拟算法，提出了一种新的非线性约束条件下的优化算法。该算法不需要人为干预，可完全实现程序化。文章以一个简单的优化实例验证了该方法的可行性。与其他优化算法和优化工具相比，该算法简洁高效、稳健通用，有较强的工程应用价值，为非线性约束条件下的优化求解提供了新的思路。%Based on Monte Carlo simulation, a new method used for optimization algorithm under non-linear constraints is presented. This method does not need human intervention and easily realizes program-integration. Its feasibility has been illustrated by a case study. Compared to other algorithms and tools, this algorithm is concise, efficient, robust and universal, and has considerable engineering value. It offers a new clue for optimization algorithm under non-linear constraints.