Learn R Programming

ConsRank (version 2.0.0)

DECORcore: Differential Evolution algorithm for Median Ranking

Description

Core function of the DECOR algorithm

Usage

DECORcore(cij, NJ, NP = 15, L = 50, FF = 0.4, CR = 0.9, FULL = FALSE)

Arguments

cij
combined input matrix
NJ
the number of judjes
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.

Value

a "list" containing the following components:
ConsR the Consensus Ranking
Tau averaged TauX rank correlation coefficient
besti matrix of best individuals for every generation
bestc vector of best individuals' cost for every gen
bests
vector of best individuals avgTau

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.