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Algorithms for Online Car-Sharing Problem

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

In the online car-sharing (a.k.a. ride-sharing) problem, we are given a set of m available car, and n requests arrive sequentially in T periods, in which each request consists of a pick-up location and a drop-off location. In each period, we must immediately and irrevocably assign free cars to serve arrived requests, such that two requests share one car. The goal is to find an online algorithm to process all requests while minimizing the total travel distance of cars. We give the first algorithm for this problem under the adversarial model and the random arrival model. For the adversarial model, we give a 2 T+ 1 / 2 -competitive algorithm, then we show this can be further improved to 2T-competitive by a carefully designed edge cost function. This almost matches the known 2 T- 1 lower bound in this model. For the random arrival model, our algorithm is 3 HT- 1 / 2 + o(1 ) -competitive, where HT is the T-th harmonic number. All the above three results are based on one single algorithm that runs in O(n3) time.

Original languageEnglish
Title of host publicationAlgorithms and Discrete Applied Mathematics - 8th International Conference, CALDAM 2022, Proceedings
EditorsNiranjan Balachandran, R. Inkulu
PublisherSpringer Science and Business Media Deutschland GmbH
Pages224-236
Number of pages13
ISBN (Print)9783030950170
DOIs
StatePublished - 2022
Event8th International Conference on Algorithms and Discrete Applied Mathematics, CALDAM 2022 - Puducherry, India
Duration: Feb 10 2022Feb 12 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13179 LNCS

Conference

Conference8th International Conference on Algorithms and Discrete Applied Mathematics, CALDAM 2022
Country/TerritoryIndia
CityPuducherry
Period02/10/2202/12/22

Keywords

  • Car-sharing
  • Competitive analysis
  • Online matching

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