{"title":"Online car-sharing problem with variable booking times","authors":"Haodong Liu, Kelin Luo, Yinfeng Xu, Huili Zhang","doi":"10.1007/s10878-024-01114-0","DOIUrl":null,"url":null,"abstract":"<p>In this paper, we address the problem of online car-sharing with variable booking times (CSV for short). In this scenario, customers submit ride requests, each specifying two important time parameters: the booking time and the pick-up time (start time), as well as two location parameters—the pick-up location and the drop-off location within a graph. For each request, it’s important to note that it must be booked before its scheduled start time. The booking time can fall within a specific interval prior to the request’s starting time. Additionally, each car is capable of serving only one request at any given time. The primary objective of the scheduler is to optimize the utilization of <i>k</i> cars to serve as many requests as possible. As requests arrive at their booking times, the scheduler faces an immediate decision: whether to accept or decline the request. This decision must be made promptly upon request submission, precisely at the booking time. We prove that no deterministic online algorithm can achieve a competitive ratio smaller than <span>\\(L+1\\)</span> even on a special case of a path (where <i>L</i> denotes the ratio between the largest and the smallest request travel time). For general graphs, we give a Greedy Algorithm that achieves <span>\\((3L+1)\\)</span>-competitive ratio for CSV. We also give a Parted Greedy Algorithm with competitive ratio <span>\\((\\frac{5}{2}L+10)\\)</span> when the number of cars <i>k</i> is no less than <span>\\(\\frac{5}{4}L+20\\)</span>; for CSV on a special case of a path, the competitive ratio of Parted Greedy Algorithm is <span>\\((2L+10)\\)</span> when <span>\\(k\\ge L+20\\)</span>.</p>","PeriodicalId":50231,"journal":{"name":"Journal of Combinatorial Optimization","volume":"16 1","pages":""},"PeriodicalIF":0.9000,"publicationDate":"2024-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Combinatorial Optimization","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1007/s10878-024-01114-0","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, we address the problem of online car-sharing with variable booking times (CSV for short). In this scenario, customers submit ride requests, each specifying two important time parameters: the booking time and the pick-up time (start time), as well as two location parameters—the pick-up location and the drop-off location within a graph. For each request, it’s important to note that it must be booked before its scheduled start time. The booking time can fall within a specific interval prior to the request’s starting time. Additionally, each car is capable of serving only one request at any given time. The primary objective of the scheduler is to optimize the utilization of k cars to serve as many requests as possible. As requests arrive at their booking times, the scheduler faces an immediate decision: whether to accept or decline the request. This decision must be made promptly upon request submission, precisely at the booking time. We prove that no deterministic online algorithm can achieve a competitive ratio smaller than \(L+1\) even on a special case of a path (where L denotes the ratio between the largest and the smallest request travel time). For general graphs, we give a Greedy Algorithm that achieves \((3L+1)\)-competitive ratio for CSV. We also give a Parted Greedy Algorithm with competitive ratio \((\frac{5}{2}L+10)\) when the number of cars k is no less than \(\frac{5}{4}L+20\); for CSV on a special case of a path, the competitive ratio of Parted Greedy Algorithm is \((2L+10)\) when \(k\ge L+20\).
期刊介绍:
The objective of Journal of Combinatorial Optimization is to advance and promote the theory and applications of combinatorial optimization, which is an area of research at the intersection of applied mathematics, computer science, and operations research and which overlaps with many other areas such as computation complexity, computational biology, VLSI design, communication networks, and management science. It includes complexity analysis and algorithm design for combinatorial optimization problems, numerical experiments and problem discovery with applications in science and engineering.
The Journal of Combinatorial Optimization publishes refereed papers dealing with all theoretical, computational and applied aspects of combinatorial optimization. It also publishes reviews of appropriate books and special issues of journals.