Journal Article10.1007/BF00247794
A data parallel augmenting path algorithm for the dense linear many-to-one assignment problem
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TL;DR: A data parallel primal-dual augmenting path algorithm for the dense linear many-to-one assignment problem also known as semi-assignment is described and it is shown that the best known sequential computational complexity of O(mn2) for dense problems, is reduced to the parallel complexity ofO(mn), on a machine with n processors supporting reductions in O(1) time.
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Abstract: The purpose of this study is to describe a data parallel primal-dual augmenting path algorithm for the dense linear many-to-one assignment problem also known as semi-assignment. This problem could for instance be described as assigning n persons to m(≤n) job groups.
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