A Greedy Randomized Adaptive Search Procedure for the Two-Partition Problem

Abstract
We present a greedy randomized adaptive search procedure (GRASP) for the network 2-partition problem. The heuristic is empirically compared with the Kernighan-Lin (K&L) method on a wide range of instances. The GRASP approach dominates K&L with respect to solution value on a large percentage of the instances tested. The ability of GRASP to find optimal solutions is assessed by comparing its performance with a general purpose mixed integer programming package.

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