pacotes <- c("dplyr","openxlsx","readxl","topsis")

if(sum(as.numeric(!pacotes %in% installed.packages())) != 0){
  instalador <- pacotes[!pacotes %in% installed.packages()]
  for(i in 1:length(instalador)) {
    install.packages(instalador, dependencies = T)
    break()}
  sapply(pacotes, require, character = T)
} else {
  sapply(pacotes, require, character = T)
}

# df <- read.xlsx("Modelo_entrada_dados.xlsx", sheet = "Exemplo_1")

# Tratamento da base de dados **************************************************
# alternatives <- df[3:nrow(df), 1]
# alternatives <- as.data.frame(alternatives)
# colnames(alternatives) <- "Alternatives"
# weights_decisor <- as.numeric(df[2, 2:ncol(df)])
# criteria_direction <- df[1, 2:ncol(df)]
# criterias <- colnames(df)[2:ncol(df)]
# matrix_decis <- as.data.frame(df[3:nrow(df), 2:ncol(df)])
# colnames(matrix_decis) <- criterias
# matrix_decis <- matrix_decis %>% mutate_all(as.numeric)

# Calcular pesos usando PSI ****************************************************
weights_psi <- function(df)
{
  alternatives <- df[3:nrow(df), 1]
  alternatives <- as.data.frame(alternatives)
  colnames(alternatives) <- "Alternatives"
  weights_decisor <- as.numeric(df[2, 2:ncol(df)])
  criteria_direction <- df[1, 2:ncol(df)]
  criterias <- colnames(df)[2:ncol(df)]
  matrix_decis <- as.data.frame(df[3:nrow(df), 2:ncol(df)])
  colnames(matrix_decis) <- criterias
  matrix_decis <- matrix_decis %>% mutate_all(as.numeric)
  matrix_decis_norm <- matrix_decis # Inicializar matrix_decis_norm

  # Normalização da Matriz de Decisão
  for(i in 1:ncol(matrix_decis_norm))
  {
    if(criteria_direction[i] == "MAX")
    {
      matrix_decis_norm[,i] <- matrix_decis[,i] / max(matrix_decis[,i])
    } else
    {
      matrix_decis_norm[,i] <- min(matrix_decis[,i]) / matrix_decis[,i]
    }
  }

  # Cálculo da variação quadrática
  pv <- rep(0, ncol(matrix_decis_norm))
  for(j in 1:ncol(matrix_decis_norm))
  {
    for(i in 1:nrow(matrix_decis_norm))
    {
      pv[j] <- pv[j] + ((matrix_decis_norm[i,j]) -
                          mean(matrix_decis_norm[,j]))^2
    }
  }
  desv_pref <- 1 - pv
  weights_PSI <- round(desv_pref / sum(desv_pref), 20)
  weights_PSI <- as.data.frame(t(weights_PSI))
  colnames(weights_PSI) <- criterias
  return(weights_PSI) # End of PSI weights calculation ************************
}

pesos_psi <- weights_psi(df)

# Ranking using PSI ************************************************************
rank_psi <- function(df, weights_PSI)
{
  alternatives <- df[3:nrow(df), 1]
  alternatives <- as.data.frame(alternatives)
  colnames(alternatives) <- "Alternatives"
  weights_decisor <- as.numeric(df[2, 2:ncol(df)])
  criteria_direction <- df[1, 2:ncol(df)]
  criterias <- colnames(df)[2:ncol(df)]
  matrix_decis <- as.data.frame(df[3:nrow(df), 2:ncol(df)])
  colnames(matrix_decis) <- criterias
  matrix_decis <- matrix_decis %>% mutate_all(as.numeric)
  matrix_decis_norm <- matrix_decis

  # Normalização da Matriz de Decisão
  for(i in 1:ncol(matrix_decis_norm))
  {
    if(criteria_direction[i] == "MAX")
    {
      matrix_decis_norm[,i] <- matrix_decis[,i] / max(matrix_decis[,i])
    } else
    {
      matrix_decis_norm[,i] <- min(matrix_decis[,i]) / matrix_decis[,i]
    }
  }

  ind_pref <- numeric(nrow(matrix_decis_norm))
  for(i in 1:nrow(matrix_decis_norm))
  {
    for(j in 1:ncol(matrix_decis_norm))
    {
      ind_pref[i] <- ind_pref[i] + matrix_decis_norm[i,j] * weights_PSI[j]
    }
  }

  rank_PSI <- matrix_decis
  rank_PSI$PSI <- ind_pref
  rank_PSI <- rank_PSI %>%
    mutate(Alternatives = alternatives) %>%
    select(Alternatives, everything()) %>% arrange(desc(PSI)) %>%
    mutate(Position = row_number()) %>%
    select(Alternatives, Position, everything())
  colnames(rank_PSI[,1]) <- "Alternatives"

  return(rank_PSI)
} # End of PSI ranking *********************************************************