License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.CP.2021.45
URN: urn:nbn:de:0030-drops-153367
URL: https://drops.dagstuhl.de/opus/volltexte/2021/15336/
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Peng, Xiao ; Solnon, Christine ; Simonin, Olivier

Solving the Non-Crossing MAPF with CP

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LIPIcs-CP-2021-45.pdf (1 MB)


Abstract

We introduce a new Multi-Agent Path Finding (MAPF) problem which is motivated by an industrial application. Given a fleet of robots that move on a workspace that may contain static obstacles, we must find paths from their current positions to a set of destinations, and the goal is to minimise the length of the longest path. The originality of our problem comes from the fact that each robot is attached with a cable to an anchor point, and that robots are not able to cross these cables.
We formally define the Non-Crossing MAPF (NC-MAPF) problem and show how to compute lower and upper bounds by solving well known assignment problems. We introduce a Variable Neighbourhood Search (VNS) approach for improving the upper bound, and a Constraint Programming (CP) model for solving the problem to optimality. We experimentally evaluate these approaches on randomly generated instances.

BibTeX - Entry

@InProceedings{peng_et_al:LIPIcs.CP.2021.45,
  author =	{Peng, Xiao and Solnon, Christine and Simonin, Olivier},
  title =	{{Solving the Non-Crossing MAPF with CP}},
  booktitle =	{27th International Conference on Principles and Practice of Constraint Programming (CP 2021)},
  pages =	{45:1--45:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-211-2},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{210},
  editor =	{Michel, Laurent D.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2021/15336},
  URN =		{urn:nbn:de:0030-drops-153367},
  doi =		{10.4230/LIPIcs.CP.2021.45},
  annote =	{Keywords: Constraint Programming (CP), Multi-Agent Path Finding (MAPF), Assignment Problems}
}

Keywords: Constraint Programming (CP), Multi-Agent Path Finding (MAPF), Assignment Problems
Collection: 27th International Conference on Principles and Practice of Constraint Programming (CP 2021)
Issue Date: 2021
Date of publication: 15.10.2021


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