Faster Sparse Minimum Cost Flow by Electrical Flow Localization

被引:9
作者
Axiotis, Kyriakos [1 ]
Madry, Aleksander [1 ]
Vladu, Adrian [2 ,3 ]
机构
[1] MIT, 77 Massachusetts Ave, Cambridge, MA 02139 USA
[2] CNRS, Paris, France
[3] IRIF, Paris, France
来源
2021 IEEE 62ND ANNUAL SYMPOSIUM ON FOUNDATIONS OF COMPUTER SCIENCE (FOCS 2021) | 2022年
关键词
minimum cost flow; interior point method; graph algorithms; electrical flows;
D O I
10.1109/FOCS52979.2021.00059
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
We give an (O) over tilde (m(3/2- 1/762) log(U + W)) time algorithm for minimum cost flow with capacities bounded by U and costs bounded by W. For sparse graphs with general capacities, this is the first algorithm to improve over the (O) over tilde (m(3/2) log(O(1))(U + W)) running time obtained by an appropriate instantiation of an interior point method [DaitchSpielman, 2008]. Our approach is extending the framework put forth in [Gao-Liu-Peng, 2021] for computing the maximum flow in graphs with large capacities and, in particular, demonstrates how to reduce the problem of computing an electrical flow with general demands to the same problem on a sublinear-sized set of vertices-even if the demand is supported on the entire graph. Along the way, we develop new machinery to assess the importance of the graph's edges at each phase of the interior point method optimization process. This capability relies on establishing a new connections between the electrical flows arising inside that optimization process and vertex distances in the corresponding effective resistance metric.
引用
收藏
页码:528 / 539
页数:12
相关论文
共 50 条
  • [21] The Complexity of Flow Expansion and Electrical Flow Expansion
    Wagner, Dorothea
    Wolf, Matthias
    SOFSEM 2021: THEORY AND PRACTICE OF COMPUTER SCIENCE, 2021, 12607 : 431 - 441
  • [22] Faster Energy Maximization for Faster Maximum Flow
    Liu, Yang P.
    Sidford, Aaron
    PROCEEDINGS OF THE 52ND ANNUAL ACM SIGACT SYMPOSIUM ON THEORY OF COMPUTING (STOC '20), 2020, : 803 - 814
  • [23] Electrical Flows, Laplacian Systems, and Faster Approximation of Maximum Flow in Undirected Graphs
    Christiano, Paul
    Kelner, Jonathan A.
    Madry, Aleksander
    Spielman, Daniel A.
    Teng, Shang-Hua
    STOC 11: PROCEEDINGS OF THE 43RD ACM SYMPOSIUM ON THEORY OF COMPUTING, 2011, : 273 - 281
  • [24] Mean-standard deviation model for minimum cost flow problem
    Gokalp, Can
    Boyles, Stephen D.
    Unnikrishnan, Avinash
    NETWORKS, 2023, 81 (03) : 378 - 398
  • [25] Determining the Minimum Cost Flow in Fuzzy Dynamic Network with GIS "ObjectLand"
    Bozhenyuk, Alexander
    Gerasimenko, Evgeniya
    Rozenberg, Igor
    2015 9TH INTERNATIONAL CONFERENCE ON APPLICATION OF INFORMATION AND COMMUNICATION TECHNOLOGIES (AICT), 2015, : 294 - 298
  • [26] APPROXIMATING THE MINIMUM-COST MAXIMUM FLOW IS P-COMPLETE
    STEIN, C
    WEIN, J
    INFORMATION PROCESSING LETTERS, 1992, 42 (06) : 315 - 319
  • [27] Toward a Fuzzy Minimum Cost Flow Problem for Damageable Items Transportation
    Lu, Si-Chao
    Wang, Xi-Fu
    FUZZY SYSTEMS AND DATA MINING II, 2016, 293 : 58 - 64
  • [28] Energy-Saving Generation Dispatch Using Minimum Cost Flow
    Zhang, Zhan'an
    Cai, Xingguo
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2015, 2015
  • [29] Heuristic solutions to robust variants of the minimum-cost integer flow problem
    Spoljarec, Marko
    Manger, Robert
    JOURNAL OF HEURISTICS, 2020, 26 (04) : 531 - 559
  • [30] A Deterministic Almost-Linear Time Algorithm for Minimum-Cost Flow
    van den Brand, Jan
    Chen, Li
    Peng, Richard
    Kyng, Rasmus
    Liu, Yang P.
    Gutenberg, Maximilian Probst
    Sachdeva, Sushant
    Sidford, Aaron
    2023 IEEE 64TH ANNUAL SYMPOSIUM ON FOUNDATIONS OF COMPUTER SCIENCE, FOCS, 2023, : 503 - 514