Strong formulations and cutting planes for designing digital data service networks

This paper deals with the problem of designing a least-cost digital data service (DDS) network that connects a given set of locations through digital switching offices with bridging capabilities. We present several alternative mixed 0–1 integer programming formulations and evaluate analytically their relative strengths by comparing their respective linear programming relaxations. By exploiting the structures inherent in a particularly strong formulation, we develop several classes of valid inequalities and cutting planes in order to tighten the initial formulation. For several problems of real-world data, computational results show that the strong formulation with valid inequalities and cutting planes generates a very tight lower bound (over 98% of the optimality) and so finds an optimal solution well within an acceptable time bound.

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