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Connectivity via convexity: Bounds on the edge expansion in graphs

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arxiv 2410.02526 v1 pith:NSIUDMX6 submitted 2024-10-03 math.OC

classification math.OC
keywords edgeexpansionboundsgraphprogramconvexificationdoublyfractional
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Convexification techniques have gained increasing interest over the past decades. In this work, we apply a recently developed convexification technique for fractional programs by He, Liu and Tawarmalani (2024) to the problem of determining the edge expansion of a graph. Computing the edge expansion of a graph is a well-known, difficult combinatorial problem that seeks to partition the graph into two sets such that a fractional objective function is minimized. We give a formulation of the edge expansion as a completely positive program and propose a relaxation as a doubly non-negative program, further strengthened by cutting planes. Additionally, we develop an augmented Lagrangian algorithm to solve the doubly non-negative program, obtaining lower bounds on the edge expansion. Numerical results confirm that this relaxation yields strong bounds and is computationally efficient, even for graphs with several hundred vertices.

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  1. The Augmented Mixing Method: Computing High-Accuracy Primal-Dual Solutions to Large-Scale SDPs via Column Updates

    math.OC 2025-07 conditional novelty 6.0 of 10

    The Augmented Mixing Method computes high-accuracy primal-dual solutions to large-scale SDPs via Burer-Monteiro factorization, inexact augmented Lagrangian, and block coordinate descent.

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