Abstract
Aggregation of constraints in a mathematical programming model is the process of replacing a set of constraints in the model by a single new constraint obtained from a combination of constraints in the set. It is generally believed that if such an aggregation step can be carried out without changing the set of feasible solutions of the problem, then it is highly desirable as it reduces the number of constraints in the model and thus makes it simpler to solve. We show that such an aggregation step may not be in general desirable for solving integer programming models by the branch and bound approach using lower bounds obtained from Linear Programming relaxation.
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