Branch-and-bound algorithm to find consensus ranking as definned by D'Ambrosio et al. (2015). If the number of objects to be ranked is large (greater than 20 or 25), it can work for very long time. Use either QuickCons or FASTcons with the option FULL=TRUE instead

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`X` |
A N by M data matrix, in which there are N judges and M objects to be judged. Each row is a ranking of the objects which are represented by the columns. The data matrix MUST contain only full rankings, or incomplete rankings, without ties.\ Alternatively X can contain the rankings observed only once. In this case the argument Wk must be used |

`Wk` |
Optional: the frequency of each ranking in the data |

`PS` |
If PS=TRUE, on the screen some information about how many branches are processed are displayed |

If the objects to be ranked is large (>15-20), it can take long time to finde the solutions

`Consensus ` |
Consensus ranking |

`Tau ` |
Averaged Kendall's Tau |

`Eltime ` |
Elapsed time in seconds |

Antonio D'Ambrosio <antdambr@unina.it>

D'Ambrosio, A., Amodio, S. & Iorio, C. (2015). Two algorithms for finding optimal solutions of the Kemeny rank aggregation problem for full rankings. Technical report, University of Naples Federico II.

FASTcons

QuickCons

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