BBTOPSIS: A bag based technique for order preference by similarity to ideal solution

Rebaï, Abdelwaheb

doi:10.1016/0165-0114(93)90343-g

Cited by 42 publications

(18 citation statements)

References 15 publications

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“…Initial efforts for extending the TOPSIS method to fuzzy sets were made by the study of Rebai [30] in which proposed the first fuzzy extension of TOPSIS method to rank alternatives using types of non-cardinal measures for measuring attributes' performance in a framework named "BBTOPSIS". However, the fuzzy extension of the TOPSIS method, used in the present study was, firstly, introduced by [24] to express the uncertainty existing in multicriteria decision support methods and specifically in the experts' judgements.…”

Section: Fuzzy Topsis Methodsmentioning

confidence: 99%

Risk Assessment Using Fuzzy TOPSIS and PRAT for Sustainable Engineering Projects

et al. 2019

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In this study, we propose a safety risk assessment process using the fuzzy extension of the technique for order of preference by similarity to ideal solution (TOPSIS) for assigning priorities to risks in worksites, in order to promote the health, safety and well-being of workers, issues that are embedded within the concept of sustainability, specifically belonging to the social sphere of sustainability. The multicriteria method works in cooperation with a simple quantitative risk analysis and assessment process, the proportional risk assessment technique (PRAT), the functionality of which is based on real data. The efficiency of this approach is validated through treating a construction project example in Greece, and the results are compared with real fatal and non-fatal accidents data for the years 2014–2016. This integrated multicriteria approach can be used by risk managers as a tool for assessing safety risks and making informed decisions about the manner that a constraint budget would be spent in order to maximize health and safety in workplace.

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Section: Fuzzy Topsis Methodsmentioning

confidence: 99%

Risk Assessment Using Fuzzy TOPSIS and PRAT for Sustainable Engineering Projects

et al. 2019

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“…ELECTRE method was applied in many decision-making environments such as the pharmaceutical industry (Varlan and Pailier, 1999), the selection of computer-aided engineering tools (Subramanian and Gershon, 1991), renewable energy planning (Beccali et al, 2003), integrated assessment of climate policy (Bell et al, 2001), and in evaluating performance in construction plants (Tam et al, 2003). The SIR, superiority and inferiority ranking, is another MCDM approach based on the theory of fuzzy bags that was proposed by Rebai (1993Rebai ( , 1994. Central to the development of this approach were the key notions of superiority, inferiority, and non-inferiority scores.…”

Section: Decision-making Modelmentioning

confidence: 99%

Public Project Programming System (3PS): a decision support system for public sector investment

Mezher

Abdul‐Malak

Arnaout³

et al. 2004

Construction Innovation

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Public investment programming is a complex exercise and involves a number of factors. These include social, economical, environmental, technological and political factors. In addition, each of the factors depends on many subfactors. For example, the economic factor depends on project impact on local and national economy, number of beneficiaries, and opportunity cost of work lost. The Public Projects Programming System (3PS) is mainly a decision support system aimed at helping senior decision makers in the public sector to program the implementation of public investment projects. A multiple criteria decision making (MCDM) approach was used based on the weighted average multi‐criteria analysis (WAMA) model. The structure (database, model base, and user interface) of the 3PS is presented. A case study, in the northern suburbs of Beirut, shows the implementation of the system in a real post conflict reconstruction environment in Lebanon.

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“…For ordinal data, Rebaï [21] defined the respective superiority score (S-score) and inferiority score (I-score) of an alternative in the set A with respect to attribute C j as…”

Section: The Topsis-mmd Methodsmentioning

confidence: 99%

“…Rebaï [21] proposed a TOPSIS variant called bag based TOPSIS (BB-TOPSIS) method. Further, some works were interested in hybridizing the TOPSIS method with other methods such as the Analytic Hierarchy Process [11], the Analytic Network Process [24], the genetic algorithms [4], the criteria importance through inter criteria correlation, CRITIC, method [15], the step-wise weight assessment ratio analysis, SWARA, method [20], the robust ordinal regression [39], etc.…”

Section: Introductionmentioning

confidence: 99%

The Meaningful Mixed Data TOPSIS (TOPSIS-MMD) Method and its Application in Supplier Selection

Aouadni¹,

Rebaï²,

Turskis³

2017

STUD INFORM CONTROL

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Abstract:The TOPSIS method suffers from two major shortcomings (1) the non-meaningfulness of the resulting rankings in mixed data contexts (i.e., the rankings of alternatives may change under admissible transformations of the initial attribute values, in the measurement-theoretic sense of the term), and (2) rank reversals or ranking irregularities(i.e., the rankings of alternatives may change if a new alternative is added to the given offered set of alternatives or an old one is deleted from it or replaced in it). The present research tackles the above shortcomings in order to improve the TOPSIS method by suggesting novel reference points and by extending it to mixed data in a rather defensible manner. Finally, the suggested TOPSIS method (referred to herein as the meaningful mixed data TOPSIS method (TOPSIS-MMD)) is used to solve a mixed data multiattribute supplier selection problem.

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BBTOPSIS: A bag based technique for order preference by similarity to ideal solution

Cited by 42 publications

References 15 publications

Risk Assessment Using Fuzzy TOPSIS and PRAT for Sustainable Engineering Projects

Risk Assessment Using Fuzzy TOPSIS and PRAT for Sustainable Engineering Projects

Public Project Programming System (3PS): a decision support system for public sector investment

The Meaningful Mixed Data TOPSIS (TOPSIS-MMD) Method and its Application in Supplier Selection

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