Random fuzzy bilevel linear programming through possibility-based value at risk model
Random fuzzy bilevel linear programming through possibility-based value at risk model
复制标题
DOI：
10.1007/s13042-012-0126-4
复制
发表时间：
2012-10
影响因子：
5.6
通讯作者：
H. Katagiri;Takeshi Uno;Kosuke Kato;H. Tsuda;H. Tsubaki
中科院分区：
文献类型：
--
作者：
H. Katagiri;Takeshi Uno;Kosuke Kato;H. Tsuda;H. Tsubaki
研究目标函数和约束中包含随机模糊变量的双层线性规划问题。引入风险值概念和可能性理论，构建了一种新的模糊随机性条件下的优化准则。提出的决策模型的目的是优化基于可能性的风险值。结果表明，将原来涉及随机模糊变量的双层规划问题转化为确定性问题。该模型的特点是在一定的凸性条件下，利用非线性双层规划技术精确求解相应的Stackelberg问题。最后给出了一个简单的数值算例，说明了该方法在实际问题中的适用性。
This article considers bilevel linear programming problems where random fuzzy variables are contained in objective functions and constraints. In order to construct a new optimization criterion under fuzziness and randomness, the concept of value at risk and possibility theory are incorporated. The purpose of the proposed decision making model is to optimize possibility-based values at risk. It is shown that the original bilevel programming problems involving random fuzzy variables are transformed into deterministic problems. The characteristic of the proposed model is that the corresponding Stackelberg problem is exactly solved by using nonlinear bilevel programming techniques under some convexity properties. A simple numerical example is provided to show the applicability of the proposed methodology to real-world hierarchical problems.