| Type: | Package |
| Title: | Compute Analytic Hierarchy Process |
| Version: | 0.1.0 |
| Maintainer: | Luciane Ferreira Alcoforado <lucianea@id.uff.br> |
| Description: | Compute a tree level hierarchy, judgment matrix, consistency index and ratio, priority vectors, hierarchic synthesis and rank. Based on the book entitled "Models, Methods, Concepts and Applications of the Analytic Hierarchy Process" by Saaty and Vargas (2012, ISBN 978-1-4614-3597-6). |
| License: | GPL-3 |
| Encoding: | UTF-8 |
| Imports: | dplyr, readxl, tidyr, ggplot2, igraph, formattable, magrittr, tibble, xlsx |
| RoxygenNote: | 7.2.2 |
| Suggests: | knitr, rmarkdown, kableExtra, stats, testthat (≥ 3.0.0) |
| Config/testthat/edition: | 3 |
| VignetteBuilder: | knitr |
| NeedsCompilation: | no |
| Packaged: | 2022-12-06 14:03:17 UTC; TPC02 |
| Author: | Luciane Ferreira Alcoforado [aut, cre], Lyncoln Sousa [aut], Orlando Celso Longo [aut], Alessandra Simão [ctb], Steven Dutt Ross [ctb], Leonardo Filgueira [ctb] |
| Repository: | CRAN |
| Date/Publication: | 2022-12-06 17:02:46 UTC |
AHPWR: Compute Analytic Hierarchy Process
Description
Compute a tree level hierarchy, judgment matrix, consistency index and ratio, priority vectors, hierarchic synthesis and rank. Based on the book entitled "Models, Methods, Concepts and Applications of the Analytic Hierarchy Process" by Saaty and Vargas (2012, ISBN 978-1-4614-3597-6).
Author(s)
Maintainer: Luciane Ferreira Alcoforado lucianea@id.uff.br
Authors:
Lyncoln Sousa lyncolnsousa@id.uff.br
Orlando Celso Longo orlandolongo@id.uff.br
Other contributors:
Alessandra Simão alessandra_simao@id.uff.br [contributor]
Steven Dutt Ross [contributor]
Leonardo Filgueira [contributor]
Pipe operator
Description
See magrittr::%>% for details.
Usage
lhs %>% rhs
Arguments
lhs |
A value or the magrittr placeholder. |
rhs |
A function call using the magrittr semantics. |
Value
The result of calling 'rhs(lhs)'.
calculates saaty's consistency index
Description
Function to calculate the saaty's consistency index
Usage
CI(m)
Arguments
m |
is a matrice of pairwise comparison |
Value
Returns saaty's consistency index
Author(s)
Luciane Ferreira Alcoforado
Examples
x=c("c1", "c2", "c3", "c4")
y=c(3, 9, 2, 8)
m=matrix_ahp(x,y)
CI(m)
x=c("a1", "a2", "a3", "a4", "a5")
y=c(1, 9, 1.5, 8, 6)
m=matrix_ahp(x,y)
CI(m)
m=diag(16)+2-2*diag(16)
m
CI(m)
CR(m)
calculates saaty's consistency ratio
Description
Function to calculate the saaty's consistency ratio
Usage
CR(m)
Arguments
m |
is a matrice of pairwise comparison |
Value
Returns saaty's consistency ratio in [0,1]
Author(s)
Luciane Ferreira Alcoforado
Examples
x=c("c1", "c2", "c3", "c4")
y=c(3, 9, 2, 8)
m=matrix_ahp(x,y)
CR(m)
x=c("a1", "a2", "a3", "a4", "a5")
y=c(1, 9, 1.5, 8, 6)
m=matrix_ahp(x,y)
CR(m)
m=diag(16)+2-2*diag(16)
m
CI(m)
CR(m)
Calculates the AHP
Description
Calculates AHP in a list of paired arrays or in a properly formatted excel worksheet stipend.
Usage
ahp(base, mapeamento, nomes_alternativas)
Arguments
base |
List of paired arrays or excel path containing the properly formatted paired arrays. |
mapeamento |
Vector containing the number of subscriptions of each criteria, from left to right. mapeamento = rep(0,n) n = number of criteria and no subcriteria; mapeamento = c(1,2) for one subcriteria in criteria 1 anda two subcriteria in criteria 2. If in doubt, see the tutorial vignette. |
nomes_alternativas |
Vector containing the names of the alternatives in your hierarchy, if not filled returns a vector of LETTERS. |
Value
Table containing the relationships of criteria, subscriptions (If any) and Alternatives Using the AHP system.
Author(s)
Lyncoln Oliveira and Luciane Ferreira Alcoforado
Examples
x=paste0(letters[3],1:5)
y=c(5,2,7,3,2)
m1=matrix_ahp(x,y)
x=paste0(letters[1],1:3)
y=c(4.4,5.2,3)
m2=matrix_ahp(x,y)
y=c(2,4,3)
m3=matrix_ahp(x,y)
y=c(4.9,5,3.3)
m4=matrix_ahp(x,y)
y=c(4.4,4.2,4.3)
m5=matrix_ahp(x,y)
y=c(5.4,5.2,5.7)
m6=matrix_ahp(x,y)
base=list(m1, m2, m3, m4, m5, m6)
mapeamento = rep(0,5)
nomes_alternativas = paste0(letters[1],1:3)
ahp(base,mapeamento, nomes_alternativas)
#with subcriteria and 3 criteria and 2 alternatives
mapeamento = c(2,0,0) #2 subcriteria in criteria 1 and 0 subcriteria to others
x=paste0(letters[3],1:3) #3 criteria
y=c(5,2,7)
m1=matrix_ahp(x,y) #compare criteria
x=paste0(letters[4],1:2)
y=c(4,6)
m2=matrix_ahp(x,y) # 2 compare 2 subcriteria of criteria 1
x=paste0(letters[1],1:2)
y=c(2,4)
m3=matrix_ahp(x,y) #alternatives for subcriteria 1
y=c(4.9,5)
m4=matrix_ahp(x,y) #alternatives for subcriteria 2
y=c(4.4,4.2)
m5=matrix_ahp(x,y) #alternatives for criteria 2
y=c(5.4,5.2)
m6=matrix_ahp(x,y) ##alternatives for criteria 3
base=list(m1, m2, m3, m4, m5, m6)
nomes_alternativas = paste0(letters[1],1:2)
ahp(base,mapeamento, nomes_alternativas)
#Other mapeamento: criteria 2 with 2 subcriteria
mapeamento = c(0,2,0)
nomes_alternativas = paste0(letters[1],1:2)
ahp(base,mapeamento, nomes_alternativas)
Calculates the AHP General
Description
Calculates AHP in a list of paired arrays or in a properly formatted excel worksheet stipend.
Usage
ahp_geral(objeto, mapeamento = "PADRAO", nomes_alternativas = "PADRAO")
Arguments
objeto |
List of paired arrays or excel path containing the properly formatted paired arrays. |
mapeamento |
Vector containing the number of subscriptions of each criteria, from left to right. If not filled the pattern and fill with 0. If in doubt, see the tutorial vignette. |
nomes_alternativas |
Vector containing the names of the alternatives in your hierarchy, if not filled returns a vector of LETTERS\[1\:qtdAlternatives\] |
Value
Table containing the relationships of criteria, subscriptions (If any) and Alternatives Using the AHP system.
Author(s)
Lyncoln Oliveira
Examples
m1=matrix(c(1, 1/5, 3, 1/5, 1/3,5, 1, 5, 3, 3,
1/3, 1/5, 1, 1/3, 1/3,5, 1/3, 3, 1, 1,3, 1/3,
3, 1, 1),ncol=5,byrow=TRUE)
m2=matrix(c(1, 1/3, 1/6, 3, 1, 1/2,6, 2, 1),nrow=3, byrow=TRUE)
m3=matrix(c(1, 1/2, 1/2,2, 1, 2, 2, 1/2, 1),nrow=3, byrow=TRUE)
m4=matrix(c(1, 1, 2,1, 1, 1, 1/2, 1, 1),nrow=3, byrow=TRUE)
m5=matrix(c(1, 2, 3,1/2, 1, 2, 1/3, 1/2, 1),nrow=3, byrow=TRUE)
m6=matrix(c(1, 5, 3,1/5, 1, 1/3, 1/3, 3, 1),nrow=3, byrow=TRUE)
base=list(m1,m2,m3,m4,m5,m6)
mapeamento=rep(0,5)
nomes_alternativas="PADRAO"
ahp_geral(base,mapeamento, nomes_alternativas)
Calculates the AHP for criteria and subcriteria
Description
Calculates AHP in a list of paired arrays or in a properly formatted excel worksheet stipend.
Usage
ahp_s(base, map)
Arguments
base |
List of paired arrays or excel path containing the properly formatted paired arrays. |
map |
Vector containing the number of subscriptions of each criteria, from left to right. map = rep(0,n) n = number of criteria and no subcriteria; mapeamento = c(1,2) for one subcriteria in criteria 1 and two subcriteria in criteria 2. If in doubt, see the tutorial vignette. |
Value
Table containing the relationships of criteria, subscriptions (If any) and Alternatives Using the AHP system.
Author(s)
Luciane Ferreira Alcoforado
Examples
x=paste0(letters[3],1:5)
y=c(5,2,7,3,2)
m1=matrix_ahp(x,y)
x=paste0(letters[1],1:3)
y=c(4.4,5.2,3)
m2=matrix_ahp(x,y)
y=c(2,4,3)
m3=matrix_ahp(x,y)
y=c(4.9,5,3.3)
m4=matrix_ahp(x,y)
y=c(4.4,4.2,4.3)
m5=matrix_ahp(x,y)
y=c(5.4,5.2,5.7)
m6=matrix_ahp(x,y)
base=list(m1, m2, m3, m4, m5, m6)
map = rep(0,5)
ahp_s(base,map)
#with two subcriteria in criteria 1 and 2 alternatives
map = c(2,0,0)
x=paste0(letters[3],1:3) #3 criteria
y=c(5,2,7)
m1=matrix_ahp(x,y) # matrix compare three criteria
x=paste0("SC1",1:2)
y=c(4,6)
m2=matrix_ahp(x,y) # 2 matrix compare two subcriteria of criteria 1
x=paste0(letters[1],1:2)
y=c(2,4)
m3=matrix_ahp(x,y) #alternatives for subcriteria 1
y=c(4.9,5)
m4=matrix_ahp(x,y) #alternatives for subcriteria 2
y=c(4.4,4.2)
m5=matrix_ahp(x,y) #alternatives for criteria 2
y=c(5.4,5.2)
m6=matrix_ahp(x,y) ##alternatives for criteria 3
base=list(m1, m2, m3, m4, m5, m6)
ahp_s(base,map)
#Other mapeamento: criteria 2 with 2 subcriteria and 3 alternatives
map = c(2,2)
x=paste0(letters[3],1:2) #2 criteria
y=c(5,7)
m1=matrix_ahp(x,y) # matrix compare two criteria
x=paste0("SC1",1:2)
y=c(4,6)
m2=matrix_ahp(x,y) # matrix compare two subcriteria of criteria 1
x=paste0(letters[1],1:3)
y=c(2,4,5)
m3=matrix_ahp(x,y) #alternatives for subcriteria 1 - criteria 1
y=c(4.9,5, 2)
m4=matrix_ahp(x,y) #alternatives for subcriteria 2 - criteria 1
y=c(4.4,8, 6)
x=paste0("SC2",1:2)
m5=matrix_ahp(x,y) #matrix compare two subcriteria of criteria 2
y=c(5.4,5.2, 1)
x=paste0(letters[1],1:3)
m6=matrix_ahp(x,y) #alternatives for subcriteria 1 - criteria 2
y=c(9,5.2, 3)
m7=matrix_ahp(x,y) #alternatives for subcriteria 2 - criteria 2
base=list(m1, m2, m3, m4, m5, m6, m7)
ahp_s(base,map)
Calculates the eigen vector of matrix
Description
Calculates the eigen vector of matrix
Usage
autoVetor(matriz)
Arguments
matriz |
a paired matrix |
Value
Returns a normalized eigenvector
Author(s)
Lyncoln Oliveira
Examples
m=diag(16)+2-2*diag(16)
m
autoVetor(m)
Calculates the priority vector of a paired matrix
Description
Calculates the priority vector of a paired array based on a list
Usage
calcula_prioridades(lista)
Arguments
lista |
a paired matrix list |
Value
Returns a list containing priority vectors for each matrix in the read list
Author(s)
Lyncoln Oliveira
creates a hierarchical structure
Description
Function to build the Diagram of hierarchies
Usage
flow_chart(names, c, a)
Arguments
names |
is a vector with names for goal, criteria and choices in this exact sequence |
c |
is a integer number of criteria, c>=2 |
a |
is a integer number of choices, a>=2 |
Value
Returns Diagram of hierarchies
Author(s)
Luciane Ferreira Alcoforado
Examples
p=flow_chart(names=NULL, a=2, c=2)
p
p=flow_chart(names=NULL, a=2, c=3)
p+ggplot2::theme_void()
flow_chart(names=c("G", "cost", "time", "hour", "home", "beach"),c=3, a=2)
Format an AHP table created by the general ahp() function
Description
Format an AHP table created by the general ahp() function
Usage
formata_tabela(tabela, cores = "PADRAO")
Arguments
tabela |
AHP table created by the general ahp() function |
cores |
Color pattern to format the table. If "PADRAO" returns the color pattern (green, blue, green or blue); if "GRAY" returns the default gray color; if "WHITE" returns the table without colors |
Value
Returns a table formatted with background colors responsive to element priority amounts
Author(s)
Lyncoln Oliveira
Format an AHP table created by the general ahp() function
Description
Format an AHP table created by the general ahp() function
Usage
formata_tabela2(tabela, cores = "PADRAO")
Arguments
tabela |
AHP table created by the general ahp() function |
cores |
Color pattern to format the table. If "PADRAO" returns the color pattern (green, blue, green or blue); if "GRAY" returns the default gray color; if "WHITE" returns the table without colors |
Value
Retorna uma tabela formatada com cores defundo responsivas as quantidades de prioridade dos elementos
Author(s)
Lyncoln Oliveira
Read an excel file containing the paired matrices and turn all your spreadsheets into a list of matrices in R
Description
Function to Read an excel file containing the paired matrices and turn all your spreadsheets into a list of matrices in Re
Usage
ler(caminho)
Arguments
caminho |
Address to an excel file that contains the worksheets |
Value
Returns a list containing the paired arrays from the excel file
Author(s)
Lyncoln Oliveira
Examples
caminho <- system.file("tests", "test_import.xlsx", package = "xlsx")
lista = ler(caminho)
creates a dataframe containing the judments holistic
Description
Function to build the judment matrix
Usage
matrix_ahp(x, y)
Arguments
x |
is a vector of names criteria or choices |
y |
is a vector of weigth scale Saaty, in [1,9] |
Value
Returns a judment matrice.
Author(s)
Luciane Ferreira Alcoforado
Examples
x=c("c1", "c2", "c3", "c4")
y=c(3, 9, 2, 8)
matrix_ahp(x,y)
x=c("a1", "a2", "a3", "a4", "a5")
y=c(1, 9, 1.5, 8, 6)
matrix_ahp(x,y)
Create paired matrix and can test saaty consistency rate
Description
Function that Create paired matrix and can test saaty consistency rate
Usage
matriz_julgamento(n_comp, CR = TRUE, n_matrix = 1)
Arguments
n_comp |
Number of elements to be evaluated |
CR |
If TRUE also returns the consistency rate of saaty, if FALSE returns only matrix |
n_matrix |
Number of matrix to be created |
Value
Returns a list with 2 positions. First position contains the paired matrices and the second position their consistency rates
Author(s)
Lyncoln Oliveira
generates vectors of weights for criteria and alternatives
Description
Function that generates vectors of weights for criteria and alternatives
Usage
normaliza(lista)
Arguments
lista |
is a list with judment matrices |
Value
Returns auxiliary list
Author(s)
Lyncoln Oliveira
Examples
lista = list(M1=diag(3), M2=diag(3)+4-4*diag(3))
normaliza(lista)
Calculates the ranking of alternatives
Description
Calculates ranking of alternatives for a list of judment matrix
Usage
ranque(tabela)
Arguments
tabela |
table building by ahp_s or ahp_geral |
Value
Table containing the ranking of alternatives
Author(s)
Lyncoln Oliveira
Examples
x=paste0(letters[3],1:5)
y=c(5,2,7,3,2)
m1=matrix_ahp(x,y)
x=paste0(letters[1],1:3)
y=c(4.4,5.2,3)
m2=matrix_ahp(x,y)
y=c(2,4,3)
m3=matrix_ahp(x,y)
y=c(4.9,5,3.3)
m4=matrix_ahp(x,y)
y=c(4.4,4.2,4.3)
m5=matrix_ahp(x,y)
y=c(5.4,5.2,5.7)
m6=matrix_ahp(x,y)
base=list(m1, m2, m3, m4, m5, m6)
mapeamento = rep(0,5)
nomes_alternativas = paste0(letters[1],1:3)
tabela = ahp(base,mapeamento, nomes_alternativas)
ranque(tabela)
#with subcriteria and 3 criteria and 2 alternatives
mapeamento = c(2,0,0) #2 subcriteria in criteria 1 and 0 subcriteria to others
x=paste0(letters[3],1:3) #3 criteria
y=c(5,2,7)
m1=matrix_ahp(x,y) #compare criteria
x=paste0(letters[4],1:2)
y=c(4,6)
m2=matrix_ahp(x,y) # 2 compare 2 subcriteria of criteria 1
x=paste0(letters[1],1:2)
y=c(2,4)
m3=matrix_ahp(x,y) #alternatives for subcriteria 1
y=c(4.9,5)
m4=matrix_ahp(x,y) #alternatives for subcriteria 2
y=c(4.4,4.2)
m5=matrix_ahp(x,y) #alternatives for criteria 2
y=c(5.4,5.2)
m6=matrix_ahp(x,y) ##alternatives for criteria 3
base=list(m1, m2, m3, m4, m5, m6)
nomes_alternativas = paste0(letters[1],1:2)
tabela = ahp(base,mapeamento, nomes_alternativas)
ranque(tabela)
organizes a table with comparison matrix data
Description
Function to organizes a table with comparison matrix data
Usage
tabela_holistica(pesos)
Arguments
pesos |
vector with holistic weights for comparison or comparison matrix data |
Value
Returns a table with assigned holistic weights, comparison matrix, priority vector and consistency ratio
Author(s)
Luciane Ferreira Alcoforado & Orlando Longo
Examples
pesos = c(3, 7, 9, 2)
names(pesos) = paste0("C",1:4)
tabela_holistica(pesos)
m = matrix_ahp(y=c(3,4,3,2.5), x=paste0("A",1:4))
tabela_holistica(pesos=m)
Transforms table with numbers into percentage with 2 decimal places
Description
Function to Transforms table with numbers into percentage with 2 decimal places
Usage
transforma_tabela(tabela)
Arguments
tabela |
table to transforms |
Value
Returns a transform table with percentage
Author(s)
Lyncoln Oliveira
Examples
tabela=data.frame(x=c(0.5, 0.25), y=c(0.55, 0.93))
transforma_tabela(tabela)
build file with judment matrices
Description
Function to buil file with judment matrices
Usage
xlsx_ahp(m, file, sheet, append)
Arguments
m |
is a matrice of pairwise comparison |
file |
is the path to the output file. |
sheet |
is a character string with the sheet name. |
append |
is a logical value indicating if m should be appended to an existing file. If TRUE the file is read from disk. |
Value
Returns a xlsx document
#m=diag(10) #file1 = xlsx_ahp(m, file = "Example_1.xlsx", sheet = "M1", append = FALSE) #file2=xlsx_ahp(m, file = "Example_1.xlsx", sheet = "M2", append = TRUE)
#see file Example_1.XLSX in working directory
Author(s)
Luciane Ferreira Alcoforado