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Discrete Applied Mathematics
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Efficient reformulation for 0-1 programs - methods and computational results

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Abstract

We introduce two general methods for 0-1 program reformulation. Our first method generalizes coefficient reduction, our second method generalizes lifting. Together they provide a unifying interpretation of many previously described automatic reformulation methods. The particular model structures that we consider are individual knapsack constraints, pairs of knapsack constraints, clique and cover induced inequalities, variable upper bounding constraints and capacity expansion constraints. We describe several easy applications of our reformulation procedures. Some computational experience is reported, including the currently best known results on a well-known 147 × 2655 benchmark problem. © 1993.

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Discrete Applied Mathematics

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