On the Complexity of Calculating Sensitivity Parameters in Boolean Programming Problems
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This article shows that, for NP-hard problems, the calculation of even the stability ball of radius 1 for an optimal solution is computationally intensive (i.e., a suitable polynomial algorithm is absent when P ≠ NP). In using greedy algorithms for solving the set covering problem (knapsack problem) with the stability radius r = O(1) , there are polynomial algorithms for calculating the stability ball of radius r for an ln m-approximate solution (1-approximate solution).
Keywordscomplexity of sensitivity analysis stability radius of a problem stability ball of radius r for an ε-approximate problem solution
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