An OWA-TOPSIS method for multiple criteria decision analysis

Abstract

A hybrid approach integrating OWA (Ordered Weighted Averaging) aggregation into TOPSIS (technique for order performance by similarity to ideal solution) is proposed to tackle multiple criteria decision analysis (MCDA) problems. First, the setting of extreme points (ideal and anti-ideal points) in TOPSIS is redefined and extended for handling the multiple extreme points situation where a decision maker (DM) or multiple DMs can provide more than one pair of extreme points. Next, three different aggregation schemes are designed to integrate OWA into the TOPSIS analysis procedure. A numerical example is provided to demonstrate the proposed approach and the results are compared for different aggregation settings and confirm the robustness of rankings from different scenarios.

Sustainability Investigation of Resource-Based Cities in Northeastern China

“…However, typically, there does not exist a unique optimal solution for such problems and it is necessary to use decision-maker's preferences to differentiate between solutions. Therefore, considering typical features such as clear and easily understandable geometric meaning, while simultaneously considering both best and worst points of view, and convenient calculation and implementation [25][26][27], TOPSIS is a popular method for solving problems in decision making [28], for example, in 2012, Behzadian et al reviewed 266 scholarly papers from 103 journals since the year 2000, and they found that TOPSIS methodology has …”

“…However, typically, there does not exist a unique optimal solution for such problems and it is necessary to use decision-maker's preferences to differentiate between solutions. Therefore, considering typical features such as clear and easily understandable geometric meaning, while simultaneously considering both best and worst points of view, and convenient calculation and implementation [25][26][27], TOPSIS is a popular method for solving problems in decision making [28], for example, in 2012, Behzadian et al reviewed 266 scholarly papers from 103 journals since the year 2000, and they found that TOPSIS methodology has been successfully applied globally to a wide range of application areas and industrial sectors with varying terms and subjects, mainly including supply chain management and logistics, design, engineering and manufacturing systems, business and marketing management, health, safety and environment management, human resources management, energy management, chemical engineering, water resources management, and other topics [29]. Recently, TOPSIS method has been applied in more subjects, for example, Çetinkaya et al applied a GIS-combined TOPSIS method to identify and rank the potential refugee camp sites for southeastern Turkey [30]; Morteza et al employed the TOPSIS obtain final priorities for the investors in tourism industries to select the optimal tourism site in a fuzzy environment in the Integrated Coastal Zone Management in Iran [31]; Dace and Blumberga applied TOPSIS as one of the three main approaches to compare the 28 European Union Member States with respect to the emission intensity of the agricultural sector [32].…”

An intuitionistic fuzzy OWA-TOPSIS method for collaborative network formation considering matching characteristics

“…Chen et al [38] generalized the OWA-TOPSIS method based on distance aggregations including internal aggregation, external aggregation I, and external aggregation II. And it need change the aggregation process when OWA-TOPSIS is extended to intuitionistic fuzzy environment.…”

Classification of Rainfall Warnings Based on the TOPSIS Method

“…Thus, understanding and compliance of assumptions are very important [39]. Conditions, rules validity and formula [40] will determine the accuracy of the results [41]. It is suggested to use this method only when there is an adequate number of criteria to make a decision on a subject [42].…”