A soft approach for hard continuous optimization
A soft approach for hard continuous optimization
复制标题
DOI：
10.1016/j.ejor.2005.01.004
复制
发表时间：
2006-08
期刊：
影响因子：
--
通讯作者：
Chunhui Xu;Peggy Ng
中科院分区：
文献类型：
--
作者：
Chunhui Xu;Peggy Ng
本文旨在介绍一种解决连续优化模型的软方法，在理论上或实践中寻求最优解是不可能的。我们首先回顾了求解连续优化模型的方法，并认为仅求解了少数具有良好结构的优化模型。为了解决更大类别的优化问题，我们通过软化求解模型的目标提出了一种软方法，并提出了实施软方法的两阶段过程。此外，我们提出了一种求解凸可行集优化模型的算法，并通过数值实验验证了软方法的有效性。
This paper is to introduce a soft approach for solving continuous optimizations models where seeking an optimal solution is theoretically or practically impossible. We first review methods for solving continuous optimization models, and argue that only a few optimization models with some good structure are solved. To solve a larger class of optimization problems, we suggest a soft approach by softening the goal in solving a model, and propose a two-stage process for implementing the soft approach. Furthermore, we offer an algorithm for solving optimization models with a convex feasible set, and verify the validity of the soft approach with numerical experiments.