Online car-sharing problem with variable booking times

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...

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Published inJournal of combinatorial optimization Vol. 47; no. 3; p. 32
Main Authors Liu, Haodong, Luo, Kelin, Xu, Yinfeng, Zhang, Huili
Format Journal Article
LanguageEnglish
Published New York Springer US 01.04.2024
Springer Nature B.V
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Online AccessGet full text
ISSN1382-6905
1573-2886
1573-2886
DOI10.1007/s10878-024-01114-0

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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 ( 3 L + 1 ) -competitive ratio for CSV. We also give a Parted Greedy Algorithm with competitive ratio ( 5 2 L + 10 ) when the number of cars k is no less than 5 4 L + 20 ; for CSV on a special case of a path, the competitive ratio of Parted Greedy Algorithm is ( 2 L + 10 ) when k ≥ L + 20 .
AbstractList 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 ( 3 L + 1 ) -competitive ratio for CSV. We also give a Parted Greedy Algorithm with competitive ratio ( 5 2 L + 10 ) when the number of cars k is no less than 5 4 L + 20 ; for CSV on a special case of a path, the competitive ratio of Parted Greedy Algorithm is ( 2 L + 10 ) when k ≥ L + 20 .
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 (52L+10) when the number of cars k is no less than 54L+20; for CSV on a special case of a path, the competitive ratio of Parted Greedy Algorithm is (2L+10) when k≥L+20.
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 $$L+1$$ 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 $$(3L+1)$$ ( 3 L + 1 ) -competitive ratio for CSV. We also give a Parted Greedy Algorithm with competitive ratio $$(\frac{5}{2}L+10)$$ ( 5 2 L + 10 ) when the number of cars k is no less than $$\frac{5}{4}L+20$$ 5 4 L + 20 ; for CSV on a special case of a path, the competitive ratio of Parted Greedy Algorithm is $$(2L+10)$$ ( 2 L + 10 ) when $$k\ge L+20$$ k ≥ L + 20 .
ArticleNumber 32
Author Luo, Kelin
Xu, Yinfeng
Liu, Haodong
Zhang, Huili
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Cites_doi 10.1007/s10878-017-0188-z
10.1007/11671411_20
10.1007/978-3-662-49529-2_17
10.4230/LIPIcs.STACS.2019.51
10.1007/978-3-030-95018-7_18
10.4230/LIPIcs.ISAAC.2018.64
10.1007/978-3-030-59901-0_5
10.4230/LIPIcs.MFCS.2018.50
10.1007/978-3-030-36412-0_27
10.1007/978-3-319-94776-1_21
ContentType Journal Article
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This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Copyright_xml – notice: This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2024
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Keywords Competitive analysis
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Car-sharing problem
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Liu H, Luo K, Xu Y, Zhang H (2019) Car-sharing problem: online scheduling with flexible advance bookings. In: Li Y, Cardei M, Huang Y (eds) Combinatorial optimization and applications-13th international conference, COCOA 2019, Xiamen, China, December 13–15, 2019, proceedings, lecture notes in computer science, vol 11949. Springer, pp 340–351. https://doi.org/10.1007/978-3-030-36412-0_27
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References_xml – reference: Lipton RJ, Tomkins A (1994) Online interval scheduling. In: Sleator DD (ed) Proceedings of the fifth annual ACM-SIAM symposium on discrete algorithms. 23–25 January 1994, Arlington, Virginia, USA. ACM/SIAM, pp 302–311. http://dl.acm.org/citation.cfm?id=314464.314506
– reference: The future of driving: Seeing the back of the car (2012) https://www.economist.com/briefing/2012/09/22/seeing-the-back-of-the-car
– reference: ChristmanAForcierWPoudelAFrom theory to practice: maximizing revenues for on-line dial-a-rideJ Comb Optim2018352512529376125010.1007/s10878-017-0188-z
– reference: Luo K, Erlebach T, Xu Y (2018a) Car-sharing between two locations: online scheduling with flexible advance bookings. In: Wang L, Zhu D (eds) Computing and combinatorics-24th international conference, COCOON 2018, Qing Dao, China, July 2–4, 2018, proceedings, lecture notes in computer science, vol 10976. Springer, pp 242–254. https://doi.org/10.1007/978-3-319-94776-1_21
– reference: Liu H, Luo K, Xu Y, Zhang H (2019) Car-sharing problem: online scheduling with flexible advance bookings. In: Li Y, Cardei M, Huang Y (eds) Combinatorial optimization and applications-13th international conference, COCOA 2019, Xiamen, China, December 13–15, 2019, proceedings, lecture notes in computer science, vol 11949. Springer, pp 340–351. https://doi.org/10.1007/978-3-030-36412-0_27
– reference: Luo K, Erlebach T, Xu Y (2018c) Online scheduling of car-sharing requests between two locations with many cars and flexible advance bookings. In: Hsu W, Lee D, Liao C (eds) 29th International symposium on algorithms and computation, ISAAC 2018, December 16–19, 2018, Jiaoxi, Yilan, Taiwan, LIPIcs, vol 123. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, pp 64:1–64:13. https://doi.org/10.4230/LIPIcs.ISAAC.2018.64
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– volume: 35
  start-page: 512
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– volume-title: Online computation and competitive analysis
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  doi: 10.1007/978-3-319-94776-1_21
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Snippet 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...
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SubjectTerms Algorithms
Automobiles
Car sharing
Combinatorics
Competition
Convex and Discrete Geometry
Customer satisfaction
Customers
Graphs
Greedy algorithms
Mathematical Modeling and Industrial Mathematics
Mathematics
Mathematics and Statistics
Operations Research/Decision Theory
Optimization
Parameters
Scheduling
Theory of Computation
Transportation services
Travel time
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Title Online car-sharing problem with variable booking times
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