2020International Journal of Industrial and Systems EngineeringRequires access

Comparison of AHP-TOPSIS and AHP-AHP methods in multi-criteria decision-making problems

Deepak Sharma, Srinivasan Sridhar, David Claudio

Open publisher page 35 citations

Abstract

Decision-making is a highly researched topic and various methods have been developed to facilitate a decision-maker (DM) in choosing the best alternative. Saaty's analytic hierarchy process (AHP) has been very popular since 1977 and has been adapted all over the world. However, AHP is a highly-debated topic. Technique for order of preference by similarity to ideal solution (TOPSIS) is another multi-criteria decision-making (MCDM) method developed by Hwang and Yoon in 1981 as a ranking method. This research is focused on identifying which is the MCDM method between AHP and TOPSIS. Since TOPSIS is a ranking method, the authors propose to combine AHP and TOPSIS methods and determine which method's ranking (AHP, AHP-TOPSIS combination, and TOPSIS with equal weights) aligns more closely with the DM's initial preference. Moreover, this research states the efficiency of the method by comparing the time it takes to make a decision and its reliability.

About this research paper

What this paper is about

Decision-making is a highly researched topic and various methods have been developed to facilitate a decision-maker (DM) in choosing the best alternative. Saaty's analytic hierarchy process (AHP) has been very popular since 1977 and has been adapted all over the world. However, AHP is a highly-debated topic. Technique for order of preference by similarity to ideal solution (TOPSIS) is another multi-criteria decision-making (MCDM) method developed by Hwang and Yoon in 1981 as a ranking method. This research is focused on identifying which is the MCDM method between AHP and TOPSIS. Since TOPSIS is a ranking method, the authors propose to combine AHP and TOPSIS methods and determine which method's ranking (AHP, AHP-TOPSIS combination, and TOPSIS with equal weights) aligns more closely with the DM's initial preference. Moreover, this research states the efficiency of the method by comparing the time it takes to make a decision and its reliability.

Why it matters

OpenAlex reports 35 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Decision-making is a highly researched topic and various methods have been developed to facilitate a decision-maker (DM) in choosing the best alternative. Saaty's analytic hierarchy process (AHP) has been very popular since 1977 and has been adapted all over the world. However, AHP is a highly-debated topic. Technique for order of preference by similarity to ideal solution (TOPSIS) is another multi-criteria decision-making (MCDM) method developed by Hwang and Yoon in 1981 as a ranking method. This research is focused on identifying which is the MCDM method between AHP and TOPSIS. Since TOPSIS is a ranking method, the authors propose to combine AHP and TOPSIS methods and determine which method's ranking (AHP, AHP-TOPSIS combination, and TOPSIS with equal weights) aligns more closely with the DM's initial preference. Moreover, this research states the efficiency of the method by comparing the time it takes to make a decision and its reliability.

Key concepts: TOPSIS, Analytic hierarchy process, Ranking (information retrieval), Multiple-criteria decision analysis, Ideal solution, Computer science, Operations research, Preference

Related papers

Back to paper searchBrowse research topicsOriginal source
Comparison of AHP-TOPSIS and AHP-AHP methods in multi-criteria decision-making problems — Research Paper | ScholarLens