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Documents authored by Zhao, Jingyang

Document
DOI: 10.4230/LIPIcs.ISAAC.2024.59
Approximation Algorithms for Cumulative Vehicle Routing with Stochastic Demands

Authors: Jingyang Zhao and Mingyu Xiao

Published in: LIPIcs, Volume 322, 35th International Symposium on Algorithms and Computation (ISAAC 2024)

Abstract
In the Cumulative Vehicle Routing Problem (Cu-VRP), we need to find a feasible itinerary for a capacitated vehicle located at the depot to satisfy customers' demand, as in the well-known Vehicle Routing Problem (VRP), but the goal is to minimize the cumulative cost of the vehicle, which is based on the vehicle’s load throughout the itinerary. If the demand of each customer is unknown until the vehicle visits it, the problem is called Cu-VRP with Stochastic Demands (Cu-VRPSD). In this paper, we propose a randomized 3.456-approximation algorithm for Cu-VRPSD, improving the best-known approximation ratio of 6 (Discret. Appl. Math. 2020). Since VRP with Stochastic Demands (VRPSD) is a special case of Cu-VRPSD, as a corollary, we also obtain a randomized 3.25-approximation algorithm for VRPSD, improving the best-known approximation ratio of 3.5 (Oper. Res. 2012). At last, we give a randomized 3.194-approximation algorithm for Cu-VRP, improving the best-known approximation ratio of 4 (Oper. Res. Lett. 2013).
Cite as

Jingyang Zhao and Mingyu Xiao. Approximation Algorithms for Cumulative Vehicle Routing with Stochastic Demands. In 35th International Symposium on Algorithms and Computation (ISAAC 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 322, pp. 59:1-59:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{zhao_et_al:LIPIcs.ISAAC.2024.59,
  author =	{Zhao, Jingyang and Xiao, Mingyu},
  title =	{{Approximation Algorithms for Cumulative Vehicle Routing with Stochastic Demands}},
  booktitle =	{35th International Symposium on Algorithms and Computation (ISAAC 2024)},
  pages =	{59:1--59:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-354-6},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{322},
  editor =	{Mestre, Juli\'{a}n and Wirth, Anthony},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ISAAC.2024.59},
  URN =		{urn:nbn:de:0030-drops-221878},
  doi =		{10.4230/LIPIcs.ISAAC.2024.59},
  annote =	{Keywords: Cumulative Vehicle Routing, Stochastic Demands, Approximation Algorithms}
}
Document
DOI: 10.4230/LIPIcs.MFCS.2022.83
Improved Approximation Algorithms for the Traveling Tournament Problem

Authors: Jingyang Zhao, Mingyu Xiao, and Chao Xu

Published in: LIPIcs, Volume 241, 47th International Symposium on Mathematical Foundations of Computer Science (MFCS 2022)

Abstract
The Traveling Tournament Problem (TTP) is a well-known benchmark problem in the field of tournament timetabling, which asks us to design a double round-robin schedule such that each pair of teams plays one game in each other’s home venue, minimizing the total distance traveled by all n teams (n is even). TTP-k is the problem with one more constraint that each team can have at most k consecutive home games or away games. The case where k = 3, TTP-3, is one of the most investigated cases. In this paper, we improve the approximation ratio of TTP-3 from (1.667+ε) to (1.598+ε), for any ε > 0. Previous schedules were constructed based on a Hamiltonian cycle of the graph. We propose a novel construction based on triangle packing. Then, by combining our triangle packing schedule with the Hamiltonian cycle schedule, we obtain the improved approximation ratio. The idea of our construction can also be extended to k ≥ 4. We demonstrate that the approximation ratio of TTP-4 can be improved from (1.750+ε) to (1.700+ε) by the same method. As an additional product, we also improve the approximation ratio of LDTTP-3 (TTP-3 where all teams are allocated on a straight line) from 4/3 to (6/5+ε).
Cite as

Jingyang Zhao, Mingyu Xiao, and Chao Xu. Improved Approximation Algorithms for the Traveling Tournament Problem. In 47th International Symposium on Mathematical Foundations of Computer Science (MFCS 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 241, pp. 83:1-83:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{zhao_et_al:LIPIcs.MFCS.2022.83,
  author =	{Zhao, Jingyang and Xiao, Mingyu and Xu, Chao},
  title =	{{Improved Approximation Algorithms for the Traveling Tournament Problem}},
  booktitle =	{47th International Symposium on Mathematical Foundations of Computer Science (MFCS 2022)},
  pages =	{83:1--83:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-256-3},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{241},
  editor =	{Szeider, Stefan and Ganian, Robert and Silva, Alexandra},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.MFCS.2022.83},
  URN =		{urn:nbn:de:0030-drops-168813},
  doi =		{10.4230/LIPIcs.MFCS.2022.83},
  annote =	{Keywords: Sports scheduling, Traveling Tournament Problem, Approximation algorithm}
}
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