A contractor prequalification model based on triangular fuzzy number and TOPSIS

Wei, Zhen Wei; Wang, Xueqing; Guo, Qing-e

doi:10.1109/icieem.2011.6035091

Cited by 6 publications

(4 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The basic concept of this method is the selected alternative should have the shortest distance fro m the positive-ideal solution and the farthest distance from the negative-ideal solution. There have been many research used this method in solving nu merous decision making problems [2], [3], [4], [1]. However, the original fuzzy TOPSIS is not always suitable to represent uncertainties due to the usage of type-1 fuzzy set (T1FS).…”

Section: One Of the Well Known Methods In Multi Criteria Decision Makmentioning

confidence: 99%

See 1 more Smart Citation

A New Entropy Weight for Sub-Criteria in Interval Type-2 Fuzzy TOPSIS and Its Application

Abdullah

Otheman²

2013

IJISA

View full text Add to dashboard Cite

Abstract-Fuzzy Technique for Order Preference bySimilarly to Ideal Solution (TOPSIS) is one of the most commonly used approaches in solving numerous mu ltip le criteria decision making problems. It has been widely used in ranking of mu lt iple alternatives with respect to mu ltiple criteria with the superiority of fu zzy set type-1 and subjective weights. Recently, fu zzy TOPSIS has been merged with interval type-2 fu zzy sets and subjective weights for criteria as to handle the wide arrays of vagueness and uncertainty. However, the role of ob jective weights in this new interval type-2 fuzzy TOPSIS has given considerably less attention. This paper aims to propose a new objective weight for sub-criteria in interval type-2 fu zzy TOPSIS. Instead of using weight for criteria, this paper considers entropy weights for sub-criteria in interval type-2 fu zzy TOPSIS method. An example of supplier select ion is used to illustrate the proposed method.

show abstract

Section: One Of the Well Known Methods In Multi Criteria Decision Makmentioning

confidence: 99%

“…Step A and 4 A are constructed respectively given in Table II, Table III and Table IV: T able 2: Evaluating values of alternatives of the decision maker 1 with respect to different attributes…”

Section: Numerical Examplementioning

confidence: 99%

A New Entropy Weight for Sub-Criteria in Interval Type-2 Fuzzy TOPSIS and Its Application

Abdullah

Otheman²

2013

IJISA

View full text Add to dashboard Cite

show abstract

“… References are as follows : 1 = Plebankiewicz (2009); 2 = Nieto-Morote and Ruz-Vila (2012); 3 = Rashvand et al (2015); 4 = Amirhosein (2013); 5 = Nasab and Ghasarian (2015); 6 = Assaf and Jannadi (1994); 7 = Mahmut et al (2002); 8 = Doloi (2009); 9 = Attar et al (2013); 10 = Plebankiewicz (2010); 11 = Doloi et al (2011); 12 = Lam et al (2000); 13 = Kog and Yaman (2016); 14 = Plebankiewicz (2012); 15 = Ossama et al (2013); 16 = Gransberg (2010); 17 = Lam and Yu (2011); 18 = Afshar et al (2017); 19 = Ka-Chi et al (2010); 20 = Wen-Haw et al (2013); 21 = Awad and Fayek (2012); 22 = Wei et al (2011); 23 = Aje (2012); 24 = El-Sawalhi et al (2007); 25 = Lam et al (2005); 26 = Goel (2016)…”

Section: Figurementioning

confidence: 99%

Review of empirical arguments on contractor pre-qualification criteria

Acheamfour

Kissi

Adjei-Kumi

et al. 2019

JEDT

View full text Add to dashboard Cite

Purpose The studies on contractor prequalification focus more on the review of models and algorithms rather than review of the criteria for contractor prequalification. However, the basis of every prequalification model primarily relates to the measurement and judgement of prospective contractors based on a set of decision criteria. This paper aims to address the gap by reviewing academic papers on contractor prequalification criteria. Design/methodology/approach A desktop search was conducted under the “T/A/K (title/abstract/keyword)” field of the Scopus search engine. A total of 49 papers were initially identified; however, only peer reviewed journals were selected for the study; therefore, a sample of 36 was subsequently used. Further filtering was done in which 26 papers were found valid for further analysis as it was realized that, not all the identified papers presented empirical arguments about the issue of contractor pre-qualification criteria. The selected 26 papers were subjected to content analysis to identify the key contractor pre-qualification criteria. Findings A total of 41 criteria were identified which were subsequently classified into six main categories, namely, technical considerations, management considerations, financial considerations, reputation considerations, general experience considerations and health, safety and environmental considerations. There was an indication that, the involvement of health, safety and environmental considerations in contractor prequalification proceedings is limited. Research limitations/implications The major limitation of this research was the limited number of papers selected for further analysis based on the Scopus search engine. The identified criteria serve as a basis for further empirical studies on contractor prequalification criteria. Practical implications The outcome of this study broadens the understanding of practitioners and researchers on the various criteria for contractor prequalification. Originality/value By critically reviewing available literature on contractor prequalification, the study sets the tone for further empirical studies on contractor prequalification.

show abstract

“…Tabla 11. Variables lingüísticas para nivel de satisfacción de las alternativas (Wei et al, 2011) Variable Las evaluaciones con términos lingüísticos de los contratistas con respecto a los criterios de evaluación cualitativa se transforman en los correspondientes números difusos. Para operar matemáticamente es necesario convertir los criterios cuantitativos que están en términos de números reales en números difusos también.…”

Section: Pesos De Los Criterios En La Etapa De Precalificaciónunclassified