Selecting the appropriate manufacturing machine is a very important and complex problem for firms which usually have to deal with both qualitative and quantitative criteria and involve different decision makers whose knowledge is often vague and imprecise. This paper proposes a peer-based modification to intuitionistic fuzzy multi-criteria group decision making with TOPSIS method (peer IF-TOPSI...

The purpose of this paper is to present an alternative of a hybrid method based on Saaty’s Analytical Hierarchy Process and on the Technique for Order Preference by using the Similarity to Ideal Solution method (AHP-TOPSIS) and, based on the AHP and its use of pairwise comparisons, to extend it to a new method called α-D MCDMTOPSIS (α-Discounting Method for multi-criteria decision making-TOPSIS...

A new deployment of the multiple criteria decision making (MCDM) techniques: the Simple Additive Weighting (SAW), and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for portfolio allocation, is demonstrated in this paper. Rather than exclusive reference to mean and variance as in the traditional mean-variance method, the criteria used in this demonstration are the f...

A new deployment of the multiple criteria decision making (MCDM) techniques: the Simple Additive Weighting (SAW), and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for portfolio allocation, is demonstrated in this paper. Rather than exclusive reference to mean and variance as in the traditional mean-variance method, the criteria used in this demonstration are the f...

Health-care waste (HCW) management is a major challenge for municipalities, particularly in the cities of developing nations. Selecting the best treatment technology for HCW can be regarded as a complex multi-criteria decision making (MCDM) issue involving a number of alternatives and multiple evaluation criteria. In addition, decision makers tend to express their personal assessments via multi...

This paper presents an efficiency assessment of African airlines, using the TOPSIS e Technique for Order Preference by Similarity to the Ideal Solution. TOPSIS is a multi-criteria decision making technique, which similar to DEA (Data Envelopment Analysis), ranks a finite set of units based on the minimisation of distance from an ideal point, and the maximisation of distance from an anti-ideal p...

In this paper, a modified TOPSIS (techniques for order preference by similarity to ideal solution) approach for solving bi-level multi-objective programming (BL-MOP) problems with fuzzy parameters is presented. These fuzzy parameters are assumed to be characterized by fuzzy numerical data, reflecting the experts' imprecise or fuzzy understanding of the nature of the parameters in the problem fo...

In this research, using technique for order-preference by similarity to ideal solution (TOPSIS) index, drought phenomenon is determined and ranked. For this purpose, using 5 atmospheric elements including temperature, wind, precipitation days, annual precipitation, precipitation concentration index (PCI), droughts occurred in Shiraz station for 20-year statistical period (1983-2003) have been d...

Interval-valued fuzzy sets involve more uncertainties than ordinary fuzzy sets and can be used to capture imprecise or uncertain decision information in fields that require multiple-criteria decision analysis (MCDA). This paper takes the simple additive weighting (SAW) method and the technique for order preference by similarity to an ideal solution (TOPSIS) as the main structure to deal with in...

The technique for order preference by similarity to ideal solution (TOPSIS) is a technique that can consider any number of measures when seeking to identify solutions close to an ideal and far from a nadir solution. TOPSIS traditionally has been applied in multiple criteria decision analysis. In this article, we propose an approach to develop a TOPSIS classifier. We demonstrate its use in credi...