Algorithms for graph partitioning on the planted partition model

Anne Condon, Richard M. Karp

Random Structures and Algorithms · 2001 · 439 citations · 15 references

Concepts

TL;DR

The NP‑hard graph bisection problem seeks to split an undirected graph into two equal groups while minimizing cross‑edges, and the more general graph l‑partition problem extends this to l equal groups with the same objective. The authors introduce a simple, linear‑time algorithm for the graph l‑partition problem and analyze its performance on a random planted l‑partition model. In the planted model, n nodes are divided into l groups of size n/l, with intra‑group edges appearing with probability p and inter‑group edges with probability r<p. They prove that if p−r≥n^{−1/2+ϵ} for some constant ϵ, the algorithm recovers the optimal partition with probability 1−exp(−nΘ(ε)). © 2001 John Wiley & Sons, Inc.; Random Structures & Algorithms, 18:116–140, 2001.

Abstract

The NP-hard graph bisection problem is to partition the nodes of an undirected graph into two equal-sized groups so as to minimize the number of edges that cross the partition. The more general graph l-partition problem is to partition the nodes of an undirected graph into l equal-sized groups so as to minimize the total number of edges that cross between groups. We present a simple, linear-time algorithm for the graph l-partition problem and we analyze it on a random "planted l-partition" model. In this model, the n nodes of a graph are partitioned into l groups, each of size n/l; two nodes in the same group are connected by an edge with some probability p, and two nodes in different groups are connected by an edge with some probability r<p. We show that if p−r≥n−1/2+ϵ for some constant ϵ, then the algorithm finds the optimal partition with probability 1− exp(−nΘ(ε)). © 2001 John Wiley & Sons, Inc. Random Struct. Alg., 18: 116–140, 2001

References

15