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Reduced Cost-Based Ranking for Generating Promising Subproblems - Milano, van Hoeve (2002) (Correct)
....which variables will contribute to the discrepancy. In the worst case they can be the k variables having the lowest c # i values. Then the best (i.e. the highest) value among these can be chosen, which corresponds to L[k] A better bound improvement can be achieved by the following theorem [22]. n , LB 0 i=1 L[i] is a valid lower bound for the subproblems corresponding to discrepancy k. Proof. The proof is based on the concept of additive bounding procedures [6, 7] that states as follows: first we solve a relaxation of a problem P . We obtain a bound LB, in our case LB 0 ....
A. Lodi. Personal communication.
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