uwTOPSIS: Unweighted TOPSIS model

#' Data: E. Jacquet-Lagreze J. Siskos  (1981).
#'
#' A subjective preference system for ten reference cars (source of criteria informations: Sp~cml Salon. L'action automobile et touristique, No. 238, octobre 1980)
#'
#' @usage data("JLS_1981")
#' @format Data frame (tibble) with 10 rows and 7 columns. The variables are:
#' \describe{
#'   \item{CarModel}{Model of the car to be evaluated.}
#'   \item{MaxSpeed}{Maximum speed (km / h).}
#'   \item{HP}{Horse Power (CV).}
#'   \item{Space}{Space inside the car (m^2).}
#'   \item{UrbanCons}{Consumption in town (l / 100 km).}
#'   \item{HighCons}{Consumption at 120 km /h (l / 100 km).}
#'   \item{Price}{Price in French francs.}
#' }
#' @source E. Jacquet-Lagreze and J. Siskos  (1981). "Assessing a set of additive utility functions for multicriteria decision-making, the UTA method", European Journal of Operational Research,  10(2), 151-164. \code{doi}: 10.1016/0377-2217(82)90155-2
#'
#' @author
#' \strong{Vicente Liern Carrion} (\email{vicente.liern@@uv.es}).
#' \emph{Department of Business Mathematics}
#'
#' \strong{Rafael Benitez} (\email{rafael.suarez@@uv.es}).
#' \emph{Department of Business Mathematics}
#'
#' University of Valencia (Spain)

"JLS_1981"


#' Data: P. Annoni, L. Dijkstra and T. E. Hellman (2016).
#'
#' Components of the three dimensions used to obtain the Social Progress Index for European Regions in 2016.
#'
#' @usage data("SPI")
#' @format Data frame (tibble) with 272 rows and 13 columns. The variables are:
#' \describe{
#'   \item{Region Code}{NUTS 1, 2 or 3 code for the European region to be evaluated.}
#'   \item{Columns 2 - 5}{Components of the "Basic Human Needs" dimension.}
#'   \item{Columns 6 - 9}{Components of the "Foundations of Wellbeing" dimension.}
#'   \item{Columns 10 - 13}{Components of the "Opportunity" dimension.}
#' }
#' @source P. Annoni, L. Dijkstra and T. E. Hellman (2016). "The EU Regional SPI: a Measure of Social Progress in the EU Regions", Methodological Paper. \code{url}: http://ec.europa.eu/regional_policy/sources/information/maps/methodological_note_eu_spi_2016.pdf. Accesed on 2020-03-08
#'
#' @author
#' \strong{Vicente Liern Carrion} (\email{vicente.liern@@uv.es}).
#' \emph{Department of Business Mathematics}
#'
#' \strong{Rafael Benitez} (\email{rafael.suarez@@uv.es}).
#' \emph{Department of Business Mathematics}
#'
#' University of Valencia (Spain)

"SPI"

#' Data: A. Oztel, A. Karakas, A. Ahmet (2018)
#'
#' Decision matrix for Green Star hotel selection problem in Turkey.
#'
#' @usage data("GShotels")
#' @format Data frame (tibble) with 35 rows and 11 columns. The variables are:
#' \describe{
#'   \item{HOTEL}{Code of the hotel.}
#'   \item{dSubway}{Distance to the closest subway station (km).}
#'   \item{dSubway}{Distance to the Airport (km).}
#'   \item{dCoachStation}{Distance to Coach Station (km).}
#'   \item{dSutanSquare}{Distance to Sultan Ahmet Square (km).}
#'   \item{Traffic}{Traffic intensity (1-4).}
#'   \item{PriceTA.}{Price given in Trip Advisor platform }
#'   \item{scTrivago}{Score given in Trivago platform (0-10)}
#'   \item{scTripAdvisor}{Score given in Trip Advisor platform (1-5)}
#'   \item{scHotels.com}{Score given in Hotels.com platform (0-10)}
#'   \item{scGoogle}{Score given in Google.com (1-5).}
#' }
#' @source Oztel A, Karakas A, Ahmet A. 2018. Green Star Hotel Selection with Fuzzy TOPSIS Method:Case of Istanbul. In: Dorczak R, Arslan H, Musialik R, editors. Recent researches on socialsciences. First edit ed. Krakow: Institute of Public Affairs - Jagiellonian University; chap.Green Star; p. 473–485.
#'
#' @author
#' \strong{Vicente Liern Carrion} (\email{vicente.liern@@uv.es}).
#' \emph{Department of Business Mathematics}
#'
#' \strong{Rafael Benitez} (\email{rafael.suarez@@uv.es}).
#' \emph{Department of Business Mathematics}
#'
#' University of Valencia (Spain)

"GShotels"