A branch-and-bound algorithm for implementing set covering model expert systems

The conventional rule-based expert system can be formulated as a 0–1, integer program, specifically, as a set covering problem. However, the implementation of an expert system in this way requires that the set covering model be solved for k-best alternate optima or near-optima. We have devised a branch-and-bound algorithm which accomplishes this. The details of the algorithm are explained in the paper. Computational results are provided.