摘要
本文针对线性双层规划问题提出一个由KMY算法演变而来的原对偶内点算法.与现在很多线性双层规划单纯型算法不同,作者提出的算法从一可行初始点穿过约束多面体内部直接得到近似最优解,当约束条件和变量数目增加时,本算法的迭代次数和计算时间变化很小.所以大大提高实际可操作性能和运算效率.
The paper presents an interior bilevel linear programming （BLP） algorithm that is based on a variant of the KMY algorithm. In contrast to the current simplex-based BLP algorithms,mov- ing through the interior of the constraint polytope in our proposed algorithm results in a solution ap- proach that is quite different and less sensitive to problem size, so providing the potential to dramat- ically improve the practical computation effectiveness.
出处
《应用数学》
CSCD
北大核心
2012年第2期467-474,共8页
Mathematica Applicata
基金
Supported by the China Nature Science Foundation(41071270)
the Natural Science Fund of Hubei Province(2010CDB03305)
the Open Fund of Hubei Province Key Laboratory of Systems Science in Metallurgical Process(C201007)
the Wuhan Chenguang Program(201150431096)
the Open Fund of State Key Laboratory of Satellite Ocean Environment Dynamics(SOED1102)
关键词
线性双层规划
原对偶势下降算法
有效解集
有效锚点
多目标线性规划
Bilevel linear programming
Primal-dual potential-reduction algorithm
Efficient solution set
Efficient anchoring points
Multiple objective linear program-ming
