3 Search Results for "Zhang, Brandon"


Document
CG Challenge
Conflict-Based Local Search for Minimum Partition into Plane Subgraphs (CG Challenge)

Authors: Jack Spalding-Jamieson, Brandon Zhang, and Da Wei Zheng

Published in: LIPIcs, Volume 224, 38th International Symposium on Computational Geometry (SoCG 2022)


Abstract
This paper examines the approach taken by team gitastrophe in the CG:SHOP 2022 challenge. The challenge was to partition the edges of a geometric graph, with vertices represented by points in the plane and edges as straight lines, into the minimum number of planar subgraphs. We used a simple variation of a conflict optimizer strategy used by team Shadoks in the previous year’s CG:SHOP to rank second in the challenge.

Cite as

Jack Spalding-Jamieson, Brandon Zhang, and Da Wei Zheng. Conflict-Based Local Search for Minimum Partition into Plane Subgraphs (CG Challenge). In 38th International Symposium on Computational Geometry (SoCG 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 224, pp. 72:1-72:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)


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@InProceedings{spaldingjamieson_et_al:LIPIcs.SoCG.2022.72,
  author =	{Spalding-Jamieson, Jack and Zhang, Brandon and Zheng, Da Wei},
  title =	{{Conflict-Based Local Search for Minimum Partition into Plane Subgraphs}},
  booktitle =	{38th International Symposium on Computational Geometry (SoCG 2022)},
  pages =	{72:1--72:6},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-227-3},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{224},
  editor =	{Goaoc, Xavier and Kerber, Michael},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SoCG.2022.72},
  URN =		{urn:nbn:de:0030-drops-160807},
  doi =		{10.4230/LIPIcs.SoCG.2022.72},
  annote =	{Keywords: local search, planar graph, graph colouring, geometric graph, conflict optimizer}
}
Document
CG Challenge
Coordinated Motion Planning Through Randomized k-Opt (CG Challenge)

Authors: Paul Liu, Jack Spalding-Jamieson, Brandon Zhang, and Da Wei Zheng

Published in: LIPIcs, Volume 189, 37th International Symposium on Computational Geometry (SoCG 2021)


Abstract
This paper examines the approach taken by team gitastrophe in the CG:SHOP 2021 challenge. The challenge was to find a sequence of simultaneous moves of square robots between two given configurations that minimized either total distance travelled or makespan (total time). Our winning approach has two main components: an initialization phase that finds a good initial solution, and a k-opt local search phase which optimizes this solution. This led to a first place finish in the distance category and a third place finish in the makespan category.

Cite as

Paul Liu, Jack Spalding-Jamieson, Brandon Zhang, and Da Wei Zheng. Coordinated Motion Planning Through Randomized k-Opt (CG Challenge). In 37th International Symposium on Computational Geometry (SoCG 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 189, pp. 64:1-64:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)


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@InProceedings{liu_et_al:LIPIcs.SoCG.2021.64,
  author =	{Liu, Paul and Spalding-Jamieson, Jack and Zhang, Brandon and Zheng, Da Wei},
  title =	{{Coordinated Motion Planning Through Randomized k-Opt}},
  booktitle =	{37th International Symposium on Computational Geometry (SoCG 2021)},
  pages =	{64:1--64:8},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-184-9},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{189},
  editor =	{Buchin, Kevin and Colin de Verdi\`{e}re, \'{E}ric},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SoCG.2021.64},
  URN =		{urn:nbn:de:0030-drops-138635},
  doi =		{10.4230/LIPIcs.SoCG.2021.64},
  annote =	{Keywords: motion planning, randomized local search, path finding}
}
Document
CG Challenge
Computing Low-Cost Convex Partitions for Planar Point Sets with Randomized Local Search and Constraint Programming (CG Challenge)

Authors: Da Wei Zheng, Jack Spalding-Jamieson, and Brandon Zhang

Published in: LIPIcs, Volume 164, 36th International Symposium on Computational Geometry (SoCG 2020)


Abstract
The Minimum Convex Partition problem (MCP) is a problem in which a point-set is used as the vertices for a planar subdivision, whose number of edges is to be minimized. In this planar subdivision, the outer face is the convex hull of the point-set, and the interior faces are convex. In this paper, we discuss and implement the approach to this problem using randomized local search, and different initialization techniques based on maximizing collinearity. We also solve small instances optimally using a SAT formulation. We explored this as part of the 2020 Computational Geometry Challenge, where we placed first as Team UBC.

Cite as

Da Wei Zheng, Jack Spalding-Jamieson, and Brandon Zhang. Computing Low-Cost Convex Partitions for Planar Point Sets with Randomized Local Search and Constraint Programming (CG Challenge). In 36th International Symposium on Computational Geometry (SoCG 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 164, pp. 83:1-83:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)


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@InProceedings{zheng_et_al:LIPIcs.SoCG.2020.83,
  author =	{Zheng, Da Wei and Spalding-Jamieson, Jack and Zhang, Brandon},
  title =	{{Computing Low-Cost Convex Partitions for Planar Point Sets with Randomized Local Search and Constraint Programming}},
  booktitle =	{36th International Symposium on Computational Geometry (SoCG 2020)},
  pages =	{83:1--83:7},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-143-6},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{164},
  editor =	{Cabello, Sergio and Chen, Danny Z.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SoCG.2020.83},
  URN =		{urn:nbn:de:0030-drops-122412},
  doi =		{10.4230/LIPIcs.SoCG.2020.83},
  annote =	{Keywords: convex partition, randomized local search, planar point sets}
}
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