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Solution of Stochastic Quadratic Programming with Imperfect Probability Distribution Using Nelder-Mead Simplex Method
| Content Provider | Semantic Scholar |
|---|---|
| Author | Ma, Xinshun Liu, Xin |
| Copyright Year | 2018 |
| Abstract | Stochastic quadratic programming with recourse is one of the most important topics in the field of optimization. It is usually assumed that the probability distribution of random variables has complete information, but only part of the information can be obtained in practical situation. In this paper, we propose a stochastic quadratic programming with imperfect probability distribution based on the linear partial information (LPI) theory. A direct optimizing algorithm based on Nelder-Mead simplex method is proposed for solving the problem. Finally, a numerical example is given to demonstrate the efficiency of the algorithm. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://file.scirp.org/pdf/JAMP_2018053010523739.pdf |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Assumed Digital Object Identifier Linear partial information Mathematical optimization Nelder–Mead method Numerical analysis Numerical method Programming model Quadratic programming Random graph Simplex algorithm |
| Content Type | Text |
| Resource Type | Article |
