Abstract
This study develops multi-parametric cost coefficient sensitivity analysis theorems for integer programs from two different algorithms: the iterative dual method proposed by Bell and Shapiro (1975) and the branch and bound algorithm. We develop post-optimality analysis theorems, which indicate that the optimal solution remains optimal if the change of cost coefficients is not less than the thresholds. The theorem implies that with information as byproduct of these two algorithms, the thresholds can be computed. We carry out numerical experiments with multi-parametric cost perturbation problems using two proposed theorems separately and compare the results and computational tractability.