Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1143315 | Operations Research Letters | 2011 | 5 Pages |
Abstract
A probabilistic constrained stochastic linear programming problem is considered, where the rows of the random technology matrix are independent and normally distributed. The quasi-concavity of the constraining function needed for the convexity of the problem is ensured if the factors of the function are uniformly quasi-concave. A necessary and sufficient condition is given for that property to hold. It is also shown, through numerical examples, that such a special problem still has practical application in optimal portfolio construction.
Related Topics
Physical Sciences and Engineering
Mathematics
Discrete Mathematics and Combinatorics
Authors
András Prékopa, Kunikazu Yoda, Munevver Mine Subasi,