目标函数系数ã€

目标函数系数ã€

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目目目目目目目目目目目目目目目目目 A 目目目目目目目目目目 夏夏夏 夏夏 夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏 目目 目 夏夏夏夏夏夏[1]夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏 A 夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏 夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏[1]夏夏夏夏夏夏夏夏夏夏夏夏夏 M 夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏 目目目 夏夏夏夏 夏夏夏夏夏 夏夏夏夏 SENSITIVITY ANALYSIS UNDER PERTURBATIONS OF OBJECTIVE FUNCTION COEFFICIENT, RIGHT-HAND SIDE AND COEFFICIENT MATRIX A Abstract: This paper improves on the single variable change in “seneitivity analysis under of both objective function coefficient and right-hand side” to the whole vector change generally, and considers the change of the coefficient matrix synchronously, and when coupled feasibility and feasibility are both dissatisfied it takes the algorithm of the got-up variable and the parameter M into the associated algorithm.The method is much easier. Keywords: Linear programming夏sensitivity analysis夏associated algorithm 夏 夏 夏夏夏夏夏夏夏夏夏min f=CX s.t. AX=b夏X 0 夏夏[1]夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏 4 夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏 夏夏夏夏[1]夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏 夏夏夏夏 A 夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏夏 [1]夏夏夏夏夏夏夏夏夏夏夏夏夏 M 夏夏夏夏夏夏夏夏夏夏夏夏 [2] [3] 夏夏 夏夏夏夏夏夏夏夏夏夏夏夏夏夏 夏夏夏夏夏夏夏夏夏夏 夏 1 夏夏夏夏夏夏 夏夏夏 1 x 2 x m x m 1 x + n x 1 x 2 x I -1 B N 1 B b - m x f 0 0 0 m 1 λ + n λ 1 B C B b -
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夏夏夏夏夏夏夏夏夏 f = 1 B C B b - 夏夏夏夏 X=夏 1 x 2 x 夏…夏 m x 夏0…,0夏 T 夏夏夏夏夏夏夏夏 B X =夏 1 x 2 x 夏…夏 m x T = 1 B b -
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