Author(s)

Xinshun Ma^*, Xin Liu

Department of Mathematics and Physics, North China Electric Power University, Baoding, China.

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.

Stochastic Quadratic Programming, LPI, Nelder-Mead

Ma, X. and Liu, X. (2018) Solution of Stochastic Quadratic Programming with Imperfect Probability Distribution Using Nelder-Mead Simplex Method. Journal of Applied Mathematics and Physics, 6, 1111-1119. doi: 10.4236/jamp.2018.65095.