A Framework for Tightening 0-1 Programs Based on Extensions of Pure 0-1 KP and SS Problems

We present a framework for automatic tightening of general 0–1 programs. A given constraint is tightened by using its own structure as well as information from other constraints. Our approach exploits special structures that are frequently encountered in industry, namely knapsack constraints, cliques, covers, variable covers, variable upper bounds and others. We consider 0–1 knapsack and subset-sum problems with clique and cover induced constraints. The tightening (reduction and increasing) of constraint coefficients benefits from implication results due to probing analysis. Some computational experience is reported.

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