{"title":"Partial Implementation of Max Flow and Min Cost Flow in Almost-Linear Time","authors":"Nithin Kavi","doi":"arxiv-2407.10034","DOIUrl":null,"url":null,"abstract":"In 2022, Chen et al. proposed an algorithm in \\cite{main} that solves the min\ncost flow problem in $m^{1 + o(1)} \\log U \\log C$ time, where $m$ is the number\nof edges in the graph, $U$ is an upper bound on capacities and $C$ is an upper\nbound on costs. However, as far as the authors of \\cite{main} know, no one has\nimplemented their algorithm to date. In this paper, we discuss implementations\nof several key portions of the algorithm given in \\cite{main}, including the\njustifications for specific implementation choices. For the portions of the\nalgorithm that we do not implement, we provide stubs. We then go through the\nentire algorithm and calculate the $m^{o(1)}$ term more precisely. Finally, we\nconclude with potential directions for future work in this area.","PeriodicalId":501216,"journal":{"name":"arXiv - CS - Discrete Mathematics","volume":"62 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Discrete Mathematics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2407.10034","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In 2022, Chen et al. proposed an algorithm in \cite{main} that solves the min
cost flow problem in $m^{1 + o(1)} \log U \log C$ time, where $m$ is the number
of edges in the graph, $U$ is an upper bound on capacities and $C$ is an upper
bound on costs. However, as far as the authors of \cite{main} know, no one has
implemented their algorithm to date. In this paper, we discuss implementations
of several key portions of the algorithm given in \cite{main}, including the
justifications for specific implementation choices. For the portions of the
algorithm that we do not implement, we provide stubs. We then go through the
entire algorithm and calculate the $m^{o(1)}$ term more precisely. Finally, we
conclude with potential directions for future work in this area.