{"title":"Sink location problems in dynamic flow grid networks","authors":"Yuya Higashikawa, Ayano Nishii, Junichi Teruyama, Yuki Tokuni","doi":"10.1016/j.tcs.2024.114812","DOIUrl":null,"url":null,"abstract":"<div><p>A <em>dynamic flow network</em> consists of a directed graph, where nodes called <em>sources</em> represent locations of evacuees, and nodes called <em>sinks</em> represent locations of evacuation facilities. Each source and each sink are given <em>supply</em> representing the number of evacuees and <em>demand</em> representing the maximum number of acceptable evacuees, respectively. Each edge is given <em>capacity</em> and <em>transit time</em>. Here, the capacity of an edge bounds the rate at which evacuees can enter the edge per unit time, and the transit time represents the time which evacuees take to travel across the edge. The <em>evacuation completion time</em> is the minimum time at which each evacuee can arrive at one of the evacuation facilities. Given a dynamic flow network without sinks, once sinks are located on some nodes or edges, the evacuation completion time for this sink location is determined. We then consider the problem of locating sinks to minimize the evacuation completion time, called the <em>sink location problem</em>. The problems have been given polynomial-time algorithms only for limited networks such as paths <span><span>[1]</span></span>, <span><span>[2]</span></span>, <span><span>[3]</span></span>, cycles <span><span>[1]</span></span>, and trees <span><span>[4]</span></span>, <span><span>[5]</span></span>, <span><span>[6]</span></span>, but no polynomial-time algorithms are known for more complex network classes. In this paper, we prove that the 1-sink location problem can be solved in polynomial-time when an input network is a grid with uniform edge capacity and transit time.</p></div>","PeriodicalId":49438,"journal":{"name":"Theoretical Computer Science","volume":"1019 ","pages":"Article 114812"},"PeriodicalIF":0.9000,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Theoretical Computer Science","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0304397524004298","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
A dynamic flow network consists of a directed graph, where nodes called sources represent locations of evacuees, and nodes called sinks represent locations of evacuation facilities. Each source and each sink are given supply representing the number of evacuees and demand representing the maximum number of acceptable evacuees, respectively. Each edge is given capacity and transit time. Here, the capacity of an edge bounds the rate at which evacuees can enter the edge per unit time, and the transit time represents the time which evacuees take to travel across the edge. The evacuation completion time is the minimum time at which each evacuee can arrive at one of the evacuation facilities. Given a dynamic flow network without sinks, once sinks are located on some nodes or edges, the evacuation completion time for this sink location is determined. We then consider the problem of locating sinks to minimize the evacuation completion time, called the sink location problem. The problems have been given polynomial-time algorithms only for limited networks such as paths [1], [2], [3], cycles [1], and trees [4], [5], [6], but no polynomial-time algorithms are known for more complex network classes. In this paper, we prove that the 1-sink location problem can be solved in polynomial-time when an input network is a grid with uniform edge capacity and transit time.
期刊介绍:
Theoretical Computer Science is mathematical and abstract in spirit, but it derives its motivation from practical and everyday computation. Its aim is to understand the nature of computation and, as a consequence of this understanding, provide more efficient methodologies. All papers introducing or studying mathematical, logic and formal concepts and methods are welcome, provided that their motivation is clearly drawn from the field of computing.