We propose a new decomposition method for large-scale linear programming. This method dualizes an (arbitrary) subset of the constraints and then maximizes the resulting dual functional by dual ascent.
In this paper we consider a class of parallel machine scheduling problems and their associated set-partitioning formulations. We show that the tightness of the linear programming relaxation of these ...
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