Abstract
A relaxation algorithm is presented for solving a class of combinatorial optimization problems called set-partitioning tasks. The convergence property of the presented algorithm is investigated theoretically. A performance guarantee is derived theoretically for the present algorithm applied to an NP-hard example problem called the maximum-cut graph partitioning. The experimental examination of its performance manifests its superiority in computational speed to the conventional gradient method.
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