ConsRank (version 2.1.5)

FASTDECOR: FAST algorithm calling DECOR

Description

FAST algorithm repeats DECOR a prespecified number of time. It returns the best solutions among the iterations

Usage

FASTDECOR(
  X,
  Wk = NULL,
  maxiter = 10,
  NP = 15,
  L = 100,
  FF = 0.4,
  CR = 0.9,
  FULL = FALSE,
  PS = TRUE
)

Value

a "list" containing the following components:

Consensus		the Consensus Ranking
Tau		averaged TauX rank correlation coefficient
Eltime		Elapsed time in seconds

Arguments

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. 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

maxiter

maximum number of iterations. Default 10

NP

The number of population individuals

L

Generations limit: maximum number of consecutive generations without improvement

FF

The scaling rate for mutation. Must be in [0,1]

CR

The crossover range. Must be in [0,1]

FULL

Default FULL=FALSE. If FULL=TRUE, the searching is limited to the space of full rankings. In this case, the data matrix must contain full rankings.

PS

Default PS=TRUE. If PS=TRUE the number of a multiple of 5 iterations is diplayed

Author

Antonio D'Ambrosio and Giulio Mazzeo

Details

This function is deprecated and it will be removed in the next release of the package. Use function 'consrank' instead.

References

D'Ambrosio, A., Mazzeo, G., Iorio, C., and Siciliano, R. (2017). A differential evolution algorithm for finding the median ranking under the Kemeny axiomatic approach. Computers and Operations Research, vol. 82, pp. 126-138.

See Also

consrank

Examples

#data(EMD)
#CR=FASTDECOR(EMD[,1:15],EMD[,16])