Improving the Smoothed Complexity of FLIP for Max Cut Problems
Improving the Smoothed Complexity of FLIP for Max Cut Problems
复制标题
提高 FLIP 最大割问题的平滑复杂度
DOI:
10.1145/3454125
复制
发表时间:
2021
影响因子:
1.3
通讯作者:
Chandrasekaran, Karthekeyan
中科院分区:
文献类型:
--
作者:
Bibak, Ali;Carlson, Charles;Chandrasekaran, Karthekeyan
Finding locally optimal solutions forMAX-CUTandMAX-k-CUTare well-known PLS-complete problems. An instinctive approach to finding such a locally optimum solution is the FLIP method. Even though FLIP requires exponential time in worst-case instances, it tends to terminate quickly in practical instances. To explain this discrepancy, the run-time of FLIP has been studied in the smoothed complexity framework. Etscheid and Röglin (ACM Transactions on Algorithms, 2017) showed that the smoothed complexity of FLIP formax-cutin arbitrary graphs is quasi-polynomial. Angel, Bubeck, Peres, and Wei (STOC, 2017) showed that the smoothed complexity of FLIP formax-cutin complete graphs is (OΦ5n15.1), where Φ is an upper bound on the random edge-weight density and Φ is the number of vertices in the input graph.While Angel, Bubeck, Peres, and Wei’s result showed the first polynomial smoothed complexity, they also conjectured that their run-time bound is far from optimal. In this work, we make substantial progress toward improving the run-time bound. We prove that the smoothed complexity of FLIP formax-cutin complete graphs isO(Φn7.83). Our results are based on a carefully chosen matrix whose rank captures the run-time of the method along with improved rank bounds for this matrix and an improved union bound based on this matrix. In addition, our techniques provide a general framework for analyzing FLIP in the smoothed framework. We illustrate this general framework by showing that the smoothed complexity of FLIP forMAX-3-CUTin complete graphs is polynomial and forMAX-k-CUTin arbitrary graphs is quasi-polynomial. We believe that our techniques should also be of interest toward showing smoothed polynomial complexity of FLIP forMAX-k-CUTin complete graphs for larger constantsk.
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DOI:
10.1007/978-3-642-22006-7_15
发表时间:
2010
期刊:
2011 Eighth International Conference on Quantitative Evaluation of SysTems
影响因子:
--
作者:
Robert Elsässer;Tobias Tscheuschner
通讯作者:
Tobias Tscheuschner
DOI:
--
发表时间:
2010
期刊:
ACM Conference on Economics and Computation
影响因子:
--
作者:
Anand Bhalgat;T. Chakraborty;S. Khanna
通讯作者:
S. Khanna
DOI:
--
发表时间:
2015
期刊:
Embedded Systems and Applications
影响因子:
--
作者:
M. Etscheid;Heiko Röglin
通讯作者:
Heiko Röglin
DOI:
10.1145/3011870
发表时间:
2017
期刊:
ACM Transactions on Algorithms (TALG)
影响因子:
--
作者:
M. Etscheid;Heiko Röglin
通讯作者:
Heiko Röglin
DOI:
10.1145/3055399.3055402
发表时间:
2016
期刊:
Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing
影响因子:
--
作者:
Omer Angel;Sébastien Bubeck;Y. Peres;F. Wei
通讯作者:
F. Wei