An evaluation of quality goals by using fuzzy AHP and fuzzy TOPSIS methodology

Tadić, Danijela; Gümüş, Alev Taşkın; Arsovski, Slavko; Aleksić, Aleksandar; Stefanović, Miladin

doi:10.3233/ifs-120659

Cited by 51 publications

(43 citation statements)

References 17 publications

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“…In this way, the fuzzy ranks of business processes are given. It can be denoted as the main difference between this paper and the papers which can be found in the literature (Tadic et al, 2013;Pak et al, 2015;Kaya and Kahraman, 2011;Hsu, 2012).…”

Section: Research Implicationsmentioning

confidence: 98%

The evaluation and enhancement of quality, environmental protection and safety in seaports

Tadić

Aleksić

Popović³

et al. 2016

Preprint

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Abstract. The evaluation and enhancement of business processes in any organization in an uncertain environment presents one of the main requirements of ISO 9000:2008, and has a key effect on competitive advantage and long-term sustainability. The aim of this paper can be defined as the identification and discussion of some of the most important business processes of seaports, and the performances of business processes and their key performance indicators (KPIs). The complexity and importance of the treated problem calls for analytic methods rather than intuitive decisions. The existing decision variables of the considered problem are described by linguistic expressions which are modelled by triangular fuzzy numbers (TFNs). In this paper, the modified fuzzy extended analytic hierarchy process (MFAHP) is proposed. The assessment of the relative importance of each pair of performances and their KPIs are stated as a fuzzy group decision making problem. By using MFAHP, the fuzzy rank of business processes of a seaport is obtained. The model is verified through an illustrative example with real life data, where the obtained data suggest measures which should enhance business strategy and improve KPIs. The future improvement is based on benchmark and knowledge sharing.

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Section: Research Implicationsmentioning

confidence: 98%

The evaluation and enhancement of quality, environmental protection and safety in seaports

Tadić

Aleksić

Popović³

et al. 2016

Preprint

Self Cite

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“…One industry association in Serbia want to investigate the situation of quality goals and to choose the finite quality goals to improve [85]. A total of 52 companies with similar business processes and with similar size are chosen as an example.…”

Section: Case Studymentioning

confidence: 99%

“…Cheng et al, proposed a method for evaluating the service quality of boutique tourist scenic spot based on TODIM [84]. In the previous study, Tadic et al proposed a TOPSIS-FAHP method to evaluate quality goals based on TOPSIS and FAHP [85]. In their study, FAHP is used to obtain the weights of attributes with the aid of the distance between two triangular fuzzy numbers [86], and TOPSIS is used to rank quality goals [87].…”

Section: Introductionmentioning

confidence: 99%

A New Evaluation Methodology for Quality Goals Extended by D Number Theory and FAHP

2020

Information

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Evaluation of quality goals is an important issue in process management, which essentially is a multi-attribute decision-making (MADM) problem. The process of assessment inevitably involves uncertain information. The two crucial points in an MADM problem are to obtain weight of attributes and to handle uncertain information. D number theory is a new mathematical tool to deal with uncertain information, which is an extension of evidence theory. The fuzzy analytic hierarchy process (FAHP) provides a hierarchical way to model MADM problems, and the comparison analysis among attributes is applied to obtain the weight of attributes. FAHP uses a triangle fuzzy number rather than a crisp number to represent the evaluation information, which fully considers the hesitation to give a evaluation. Inspired by the features of D number theory and FAHP, a D-FAHP method is proposed to evaluate quality goals in this paper. Within the proposed method, FAHP is used to obtain the weight of each attribute, and the integration property of D number theory is carried out to fuse information. A numerical example is presented to demonstrate the effectiveness of the proposed method. Some necessary discussions are provided to illustrate the advantages of the proposed method.

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“…analytic hierarchy process (AHP) Ren et al, 2015a), analytic network process (ANP) (Kilic et al, 2015), Delphi (Makkonen, 2016)), fuzzy set theory (e.g. fuzzy AHP (Tadic et al, 2013;, fuzzy ANP (Ren et al, 2015b)), etc. For these methods, indicator weights are mostly determined by experts' opinions.…”

Section: Attribute Reduction and Weighting Based On Rsmentioning

confidence: 99%

Assessing industrial ecosystem vulnerability in the coal mining area under economic fluctuations

Wang

Zheng

Song

et al. 2017

Journal of Cleaner Production

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In the context of the depth adjustment of the global economy and wild fluctuations in energy prices, the vulnerability issue of the coal mining industrial ecosystem (CMIES) has seriously affected the sustainable development of the regional economy. Comparisons of CMIES health status at a regional level are worthy of being conducted. This not only contributes to understanding a particular coal mining area's situation in regards to CMIES vulnerability, but also helps to discover a meaningful benchmark to learn the experiences in terms of action programmes formulation. In this study, based on the analysis of the vulnerability response mechanism of CMIES to economic fluctuations, an initial indicator system for vulnerability assessment of CMIES was constructed. Ultimately, 14 vulnerability-evaluating indicators and their weights were obtained using rough set attribute reduction. Based on a composite CMIES Vulnerability Index (CVI), the Rough Set-Technique for Order Preference by Similarity to Ideal Solution-Rank-sum Ratio (RS-TOPSIS-RSR) methodology is proposed to conduct the CMIES vulnerability assessment process from an overall perspective. Using this methodology, 33 coal mining areas in China are ranked as well as grouped into three specific groups based on the CVI score. The results demonstrate the feasibility of the proposed method as a valuable tool for decision making and performance evaluation with multiple alternatives and criteria.

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An evaluation of quality goals by using fuzzy AHP and fuzzy TOPSIS methodology

Cited by 51 publications

References 17 publications

The evaluation and enhancement of quality, environmental protection and safety in seaports

The evaluation and enhancement of quality, environmental protection and safety in seaports

A New Evaluation Methodology for Quality Goals Extended by D Number Theory and FAHP

Assessing industrial ecosystem vulnerability in the coal mining area under economic fluctuations

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