--- title: "AHP-TOPSIS-2N Example" author: "Raquel Dourado Coutinho, Marcos dos Santos" date: '`r Sys.Date()`' output: rmarkdown::html_vignette: toc: yes toc_depth: 2 vignette: > %\VignetteIndexEntry{AHP-TOPSIS-2N Example} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} --- ```{r, include = FALSE} knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ``` ## Introduction ##### Multicriteria Decision Analysis (MCDA) and the AHP-TOPSIS-2N method. The objective of MCDA is to assist in decisions with multiple criteria. Multicriteria methods can be useful in several problems in business and even in personal life. AHP-TOPSIS-2N is a hybrid method build from the AHP (Analytic Hierarchy Process) and TOPSIS-2N (Technique for Order of Preference by Similarity to Ideal Solution - with two normalizations). AHP-TOPSIS-2N uses the AHP to calculate the criteria weights and uses TOPSIS twice to generate rankings, each time with a different kind of normalization. This can allow the comparison of results and the analysis of the robustness. A consistency ratio is calculated, and when it is higher than 10%, it is required to check judgments on criteria comparison. ## Example As an example, this vignette uses a case of row material supplier evaluation. The goal is to choose among A, B, and C suppliers based on the product cost, product quality (1 to 5), and the lead time. Below we have the decision matrix (alternatives x criteria). | Alternatives | Cost | Quality | Lead Time| |:------------:|-----:|--------:|---------:| | A1 | 1100| 5 | 25 | | A2 | 850| 3.5 | 10 | | A3 | 950| 4 | 30 | After defining the decision matrix, it's time to define a matrix with a pairwise comparison of the criteria, using the Saaty scale (1-9). | | Cost | Quality | Lead Time| |:-----------:|-----:|--------:|---------:| | Cost | 1| 1 | 3 | | Quality | 1| 1 | 5 | | Lead Time | 1/3| 1/5 | 1 | The criteria comparison matrix can be read like this: "Cost is so important as Quality, Cost has moderate importance over Lead Time, Quality has strong importance over Lead Time." ```{r setup} library(ahptopsis2n) # define the decision matrix decision<-matrix(c(1100, 5, 25, 850, 3.5, 10, 950, 4, 30), ncol=3, byrow=TRUE) rownames(decision)<- c("A1", "A2", "A3") #define criteria matrix with pairwise comparison criteria<-matrix(c(1, 1, 3, 1, 1, 5, 1/3, 1/5, 1), ncol=3, byrow=TRUE) # define each criterion objective minmax<-c("min", "max", "min") # associate the objects to the function arguments and run the function ahptopsis2n(decision=decision, criteria=criteria, minmax=minmax) ``` As we can see, the result is a list with a consistency ratio and two data frames with priority sorting of the alternatives. ### References De Souza, L. P., Gomes, C. F. S. and De Barros, A. P. (2018). Implementation of New Hybrid AHP–TOPSIS-2N Method in Sorting and Prioritizing of an it CAPEX Project Portfolio. International Journal of Information Technology & Decision Making. DOI: 10.1142/S0219622018500207. Saaty, T.L. The Analytic Hierarchy Process. McGraw-Hill, New York. (1980)