An extension of TOPSIS for group decision making

Shih, Hsu-Shih; Shyur, Huan‐Jyh; Lee, E. Stanley

doi:10.1016/j.mcm.2006.03.023

Cited by 1,139 publications

(607 citation statements)

References 24 publications

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“…The rating which are different from what is reported in the literature are highlighted. It is observed that the energy indicator ranks the alternative almost similar to the ranking based on extended TOPSIS (Shih et al, 2007). The reason being the terms in the decision matrix of extended TOPSIS are similar to what we defined as energy.…”

Section: Example 61 Human Resource Selection In Crisp Environmentsupporting

confidence: 52%

“…The alternatives are ranked in terms of energy and exergy indicators. The ranking obtained from the thermodynamical indicators is then compared with that reported in Shih et al (2007).…”

Section: Example 61 Human Resource Selection In Crisp Environmentmentioning

confidence: 99%

“…The applications of MCDM are numerous and it has been applied to human resource management (Shih et al, 2007), transportation (Tsaur et al, 2002), portfolio optimization (Ehrgott et al, 2004), product design (Liu, 2011), vendor selection (Shyur and Shih, 2006) and visual inspection (Verma et al, 2015). The most commonly used method for MCDM is Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS).…”

Section: Introductionmentioning

confidence: 99%

“…The most commonly used method for MCDM is Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The advantages of TOPSIS includes (Shih et al, 2007) -scalar value accounting for both best and worst alternative; logical representation of human rationale and easy implementation. TOPSIS is based upon the concept that the chosen solution should be closest to positive ideal solution and farthest from negative ideal solution.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A thermodynamical approach towards group multi-criteria decision making (GMCDM) and its application to human resource selection

Verma

Rajasankar

2017

Applied Soft Computing

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In multi-criteria decision making (MCDM) problems, ratings are assigned to the alternatives on different criteria by the expert group. In this paper, we propose a thermodynamically consistent model for MCDM using the analogies for thermodynamical indicators -energy, exergy and entropy. The most commonly used method for analysing MCDM problem is Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The conventional TOPSIS method uses a measure similar to that of energy for the ranking of alternatives. We demonstrate that the ranking of the alternatives is more meaningful if we use exergy in place of energy. The use of exergy is superior due to the inclusion of a factor accounting for the quality of the ratings by the expert group. The unevenness in the ratings by the experts is measured by entropy. The procedure for the calculation of the thermodynamical indicators is explained in both crisp and fuzzy environment. Finally, two case studies are carried out to demonstrate effectiveness of the proposed model.

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Section: Example 61 Human Resource Selection In Crisp Environmentsupporting

confidence: 52%

“…The alternatives are ranked in terms of energy and exergy indicators. The ranking obtained from the thermodynamical indicators is then compared with that reported in Shih et al (2007).…”

Section: Example 61 Human Resource Selection In Crisp Environmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A thermodynamical approach towards group multi-criteria decision making (GMCDM) and its application to human resource selection

Verma

Rajasankar

2017

Applied Soft Computing

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“…According to [19] and [20], TOPSIS has the following three advantages: (i) a sound logic that represents the rationale of individual choice; (ii) a scalar value that record for both the best and worst alternatives concurrently; and (iii) a straightforward computation algorithm that can be easily programmed into a spreadsheet. These advantages make TOPSIS a popular MCDM technique as compared with other related techniques such as AHP and ELECTRE [21].…”

Section: Introductionmentioning

confidence: 99%

Interactive TOPSIS Based Group Decision Making Methodology Using Z-Numbers

Yaakob¹,

Gegov²

2016

IJCIS

101

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The ability in providing result that is consistent with actual ranking remains the major concern in group decision making environment. The main aim of this paper is to introduce a novel modification of TOPSIS method to facilitate multi criteria decision making problems based on the concept of Z-numbers called Z-TOPSIS. The proposed method is adequate and intuitive in giving meaningful structure for formalizing information of a decision making problem, as it takes into account the decision makers' reliability. This study also provides bridge with some established knowledge in fuzzy sets to certain extend as to strengthen the concept of ranking alternatives using Znumbers. To ensure practicality and effectiveness of proposed method, stock selection problem is studied. The ranking based on proposed method is validated comparatively using spearman rho rank correlation. Based on the analysis, the proposed method outperforms the established TOPSIS methods in term of ranking performance.

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