Constant-Factor Approximation Algorithms for Parity-Constrained Facility Location and k-Center

被引:0
|
作者
Kangsan Kim
Yongho Shin
Hyung-Chan An
机构
[1] Devsisters Corp.,Department of Computer Science
[2] Yonsei University,undefined
来源
Algorithmica | 2023年 / 85卷
关键词
Facility location problems; Approximation algorithms; -center; Parity constraints; Clustering problems; Theory of computation Approximation algorithms analysis; Theory of computation Facility location and clustering;
D O I
暂无
中图分类号
学科分类号
摘要
Facility location is a prominent optimization problem that has inspired a large quantity of both theoretical and practical studies in combinatorial optimization. Although the problem has been investigated under various settings reflecting typical structures within the optimization problems of practical interest, little is known on how the problem behaves in conjunction with parity constraints. This shortfall of understanding was rather discouraging when we consider the central role of parity in the field of combinatorics. In this paper, we present the first constant-factor approximation algorithm for the facility location problem with parity constraints. We are given as the input a metric on a set of facilities and clients, the opening cost of each facility, and the parity requirement–odd\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\textsf{odd}$$\end{document}, even\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\textsf{even}$$\end{document}, or unconstrained\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\textsf{unconstrained}$$\end{document}–of every facility in this problem. The objective is to open a subset of facilities and assign every client to an open facility so as to minimize the sum of the total opening costs and the assignment distances, but subject to the condition that the number of clients assigned to each open facility must have the same parity as its requirement. Although the unconstrained facility location problem as a relaxation for this parity-constrained generalization has unbounded gap, we demonstrate that it yields a structured solution whose parity violation can be corrected at small cost. This correction is prescribed by a T-join on an auxiliary graph constructed by the algorithm. This auxiliary graph does not satisfy the triangle inequality, but we show that a carefully chosen set of shortcutting operations leads to a cheap and sparseT-join. Finally, we bound the correction cost by exhibiting a combinatorial multi-step construction of an upper bound. We also consider the parity-constrained k-center problem, the bottleneck optimization variant of parity-constrained facility location. We present the first constant-factor approximation algorithm also for this problem.
引用
收藏
页码:1883 / 1911
页数:28
相关论文
共 42 条
  • [21] Parameterized Approximation Algorithms and Lower Bounds for k-Center Clustering and Variants
    Bandyapadhyay, Sayan
    Friggstad, Zachary
    Mousavi, Ramin
    ALGORITHMICA, 2024, 86 (08) : 2557 - 2574
  • [22] Improved Approximation Algorithms for Capacitated Fault-Tolerant k-Center
    Cristina G. Fernandes
    Samuel P. de Paula
    Lehilton L. C. Pedrosa
    Algorithmica, 2018, 80 : 1041 - 1072
  • [23] A constant-factor approximation algorithm for the geometric k-MST problem in the plane
    Mitchell, JSB
    Blum, A
    Chalasani, P
    Vempala, S
    SIAM JOURNAL ON COMPUTING, 1998, 28 (03) : 771 - 781
  • [24] A Constant-Factor Bi-Criteria Approximation Guarantee for k-means plus
    Wei, Dennis
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 29 (NIPS 2016), 2016, 29
  • [25] Approximation algorithms for minimum-load k-facility location
    Ahmadian S.
    Behsaz B.
    Friggstad Z.
    Jorati A.
    Salavatipour M.R.
    Swamy C.
    2018, Association for Computing Machinery, 2 Penn Plaza, Suite 701, New York, NY 10121-0701, United States (14)
  • [26] Approximation Algorithms for Minimum-Load k-Facility Location
    Ahmadian, Sara
    Behsaz, Babak
    Friggstad, Zachary
    Jorati, Amin
    Salavatipour, Mohammad R.
    Swamy, Chaitanya
    ACM TRANSACTIONS ON ALGORITHMS, 2018, 14 (02)
  • [27] Approximation algorithms for the dynamic k-level facility location problems
    Wang, Limin
    Zhang, Zhao
    Wu, Chenchen
    Xu, Dachuan
    Zhang, Xiaoyan
    THEORETICAL COMPUTER SCIENCE, 2021, 853 : 43 - 56
  • [28] Approximation algorithms for hard capacitated k-facility location problems
    Aardal, Karen
    van den Berg, Pieter L.
    Gijswijt, Dion
    Li, Shanfei
    EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2015, 242 (02) : 358 - 368
  • [29] Approximation algorithms for k-level stochastic facility location problems
    Melo, Lucas P.
    Miyazawa, Flavio K.
    Pedrosa, Lehilton L. C.
    Schouery, Rafael C. S.
    JOURNAL OF COMBINATORIAL OPTIMIZATION, 2017, 34 (01) : 266 - 278
  • [30] Approximation algorithms for k-level stochastic facility location problems
    Lucas P. Melo
    Flávio K. Miyazawa
    Lehilton L. C. Pedrosa
    Rafael C. S. Schouery
    Journal of Combinatorial Optimization, 2017, 34 : 266 - 278