Continuous iterative algorithms for anti-Cheeger cut

Fuente: arXiv
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Autores principales: Shao, Sihong, Yang, Chuan
Formato: Preprint
Publicado: 2021
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author Shao, Sihong
Yang, Chuan
author_facet Shao, Sihong
Yang, Chuan
contents As a judicious correspondence to the classical maxcut, the anti-Cheeger cut has more balanced structure, but few numerical results on it have been reported so far. In this paper, we propose a continuous iterative algorithm (CIA) for the anti-Cheeger cut problem through fully using an equivalent continuous formulation. It does not need rounding at all and has advantages that all subproblems have explicit analytic solutions, the objective function values are monotonically updated and the iteration points converge to a local optimum in finite steps via an appropriate subgradient selection. It can also be easily combined with the maxcut iterations for breaking out of local optima and improving the solution quality thanks to the similarity between the anti-Cheeger cut problem and the maxcut problem. The performance of CIAs is fully demonstrated through numerical experiments on G-set from two aspects: one is on the solution quality where we find that the approximate solutions obtained by CIAs are of comparable quality to those by the multiple search operator heuristic method; the other is on the computational cost where we show that CIAs always run faster than the often-used continuous iterative algorithm based on the rank-two relaxation.
format Preprint
id arxiv_https___arxiv_org_abs_2103_10705
institution arXiv
publishDate 2021
record_format arxiv
spellingShingle Continuous iterative algorithms for anti-Cheeger cut
Shao, Sihong
Yang, Chuan
Optimization and Control
Numerical Analysis
Combinatorics
90C27, 05C85, 65K10, 90C26, 90C32
As a judicious correspondence to the classical maxcut, the anti-Cheeger cut has more balanced structure, but few numerical results on it have been reported so far. In this paper, we propose a continuous iterative algorithm (CIA) for the anti-Cheeger cut problem through fully using an equivalent continuous formulation. It does not need rounding at all and has advantages that all subproblems have explicit analytic solutions, the objective function values are monotonically updated and the iteration points converge to a local optimum in finite steps via an appropriate subgradient selection. It can also be easily combined with the maxcut iterations for breaking out of local optima and improving the solution quality thanks to the similarity between the anti-Cheeger cut problem and the maxcut problem. The performance of CIAs is fully demonstrated through numerical experiments on G-set from two aspects: one is on the solution quality where we find that the approximate solutions obtained by CIAs are of comparable quality to those by the multiple search operator heuristic method; the other is on the computational cost where we show that CIAs always run faster than the often-used continuous iterative algorithm based on the rank-two relaxation.
title Continuous iterative algorithms for anti-Cheeger cut
topic Optimization and Control
Numerical Analysis
Combinatorics
90C27, 05C85, 65K10, 90C26, 90C32
url https://arxiv.org/abs/2103.10705