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  1. Home > Articles & Issues >
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  3. Token Swapping on Tr ...
Article

Token Swapping on Trees

Ahmad Biniaz, Kshitij Jain, Anna Lubiw, Zuzana Masárová, Tillmann Miltzow, Debajyoti Mondal, Anurag Murty Naredla, Josef Tkadlec ORCID, Alexi Turcotte
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Open on arXiv
Submitted on
August 23, 2021
Accepted on
October 15, 2022
Published on
January 18, 2023
Last modified on
March 27, 2025
Volume 24
vol. 24:2
Discrete Algorithms
DOI
10.46298/dmtcs.8383
License
arXiv.org - Non-exclusive license to distribute
Natural Sciences and Engineering Research Council of Canada
Indicators
1480
Views
1484
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Token Swapping on Trees

Ahmad Biniaz, Kshitij Jain, Anna Lubiw, Zuzana Masárová, Tillmann Miltzow, Debajyoti Mondal, Anurag Murty Naredla, Josef Tkadlec ORCID, Alexi Turcotte
Abstract
The input to the token swapping problem is a graph with vertices $v_1, v_2, \ldots, v_n$, and $n$ tokens with labels $1, 2, \ldots, n$, one on each vertex. The goal is to get token $i$ to vertex $v_i$ for all $i= 1, \ldots, n$ using a minimum number of swaps, where a swap exchanges the tokens on the endpoints of an edge. We present some results about token swapping on a tree, also known as "sorting with a transposition tree": 1. An optimum swap sequence may need to perform a swap on a leaf vertex that has the correct token (a "happy leaf"), disproving a conjecture of Vaughan. 2. Any algorithm that fixes happy leaves -- as all known approximation algorithms for the problem do -- has approximation factor at least $4/3$. Furthermore, the two best-known 2-approximation algorithms have approximation factor exactly 2. 3. A generalized problem -- weighted coloured token swapping -- is NP-complete on trees, even when they are restricted to be subdivided stars, but solvable in polynomial time on paths and stars. In this version, tokens and vertices have colours, and colours have weights. The goal is to get every token to a vertex of the same colour, and the cost of a swap is the sum of the weights of the two tokens involved. Comment: 37 pages, Discrete Mathematics and Theoretical Computer Science, DMTCS vol. 24:2, 2022, #9
Keywords
  • Computer Science - Computational Complexity
  • Computer Science - Data Structures and Algorithms
  • 03D15, 05C05, 68R05
  • F.2.0
Mathematics Subject Classification 2020
  • 05A05 - Permutations, words, matrices
  • 05C05 - Trees
  • 05C25 - Graphs and abstract algebra (groups, rings, fields, etc.)
  • 05C85 - Graph algorithms (graph-theoretic aspects)
  • 68P10 - Searching and sorting
  • 68Q17 - Computational difficulty of problems (lower bounds, completeness, difficulty of approximation, etc.)
  • 68Q25 - Analysis of algorithms and problem complexity
  • 68R10 - Graph theory (including graph drawing) in computer science
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