A soft approach for hard continuous optimization

A soft approach for hard continuous optimization

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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: ,
Keywords: statistics: sampling
Abstract:

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.

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