A concentration inequality for the facility location problem

被引:1
|
作者
Silwal, Sandeep [1 ]
机构
[1] MIT, 77 Massachusetts Ave, Cambridge, MA 02139 USA
关键词
Facility location; Concentration inequality; Stochastic optimization; MINIMAL SPANNING TREE; RANDOM K-SAT; LIMIT;
D O I
10.1016/j.orl.2022.01.009
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
We give a concentration inequality for a stochastic version of the facility location problem. We show the objective C-n = min(F subset of[0, 1]2) vertical bar F vertical bar + Sigma(x is an element of X )min(f is an element of F) parallel to x - f parallel to is concentrated in an interval of length O (n(1/6)) and E[C-n] = Theta(n(2/3)) if the input X consists of i.i.d. uniform points in the unit square. Our main tool is to use a geometric quantity, previously used in the design of approximation algorithms for the facility location problem, to analyze a martingale process. Many of our techniques generalize to other settings. (C) 2022 Elsevier B.V. All rights reserved.
引用
收藏
页码:213 / 217
页数:5
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