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binary integer programming; decision-theoretic troubleshooting
We deal with a sequencing problem that arises when there are multiple repair actions available to fix a broken man-made system and the true cause of the system failure is uncertain. The system is formally described by a probabilistic model, and it is to be repaired by a sequence of troubleshooting actions designed to identify the cause of the malfunction and fix the system. The task is to find a course of repair with minimal expected cost. We propose a binary integer programming formulation for the problem. This can be used to solve the problem directly or to compute lower bounds of the minimal expected cost using linear programming relaxation. We also present three greedy algorithms for computing initial feasible solutions.
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