DECORcore

The number of population individuals

Generations limit: maximum number of consecutive generations without improvement

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

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

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.

FULL

Core function of the DECOR algorithm

Compute the median ranking according to the Kemeny's axiomatic approach.
Rankings can or cannot contain ties, rankings can be both complete or incomplete.
The package contains both branch-and-bound algorithms and heuristic solutions recently proposed.
The package also provide some useful utilities for deal with preference rankings.
Essential references:
Emond, E.J., and Mason, D.W. (2002) <doi:10.1002/mcda.313>;
D'Ambrosio, A., Amodio, S., and Iorio, C. (2015) <doi:10.1285/i20705948v8n2p198>;
Amodio, S., D'Ambrosio, A., and Siciliano R. (2016) <doi:10.1016/j.ejor.2015.08.048>;
D'Ambrosio, A., Mazzeo, G., Iorio, C., and Siciliano, R. (2017) <doi:10.1016/j.cor.2017.01.017>.

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

DECORcore: Differential Evolution algorithm for Median Ranking

Description

Usage

Arguments

Value

References