Article ID: | iaor20084107 |
Country: | Netherlands |
Volume: | 173 |
Issue: | 1 |
Start Page Number: | 18 |
End Page Number: | 29 |
Publication Date: | Aug 2006 |
Journal: | European Journal of Operational Research |
Authors: | Xu Chunhui, Ng Peggy |
Keywords: | statistics: sampling |
This paper is to introduce a soft approach for solving continuous optimization 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.