Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Erschienen in:
Fine–Kinney Occupational Risk Assessment Method and Its Extensions by Fuzzy Sets: A State-of-the-Art Review Kapitel lesen Erstes Kapitel lesen

2021 | OriginalPaper | Buchkapitel

8. Fine–Kinney-Based Occupational Risk Assessment Using Interval Type-2 Fuzzy QUALIFLEX

verfasst von : Assoc. Prof. Muhammet Gul, Assoc. Prof. Suleyman Mete, Assist. Prof. Faruk Serin, Assoc. Prof. Erkan Celik

Erschienen in: Fine–Kinney-Based Fuzzy Multi-criteria Occupational Risk Assessment

Verlag: Springer International Publishing

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

In this chapter, we improved Fine–Kinney occupational risk assessment approach with interval type-2 fuzzy QUALIFLEX (IT2FQUALIFLEX). QUALIFLEX is an outranking multi-attribute decision-making method proposed by an extension of the Paelinck’s (Pap Reg Sci Assoc 36:59–74,[1]), generalized Jacquet-Lagreze’s permutation method. Similar to other outranking solution-based approaches, it considers the solution which is a comparison of hazards. In this chapter, we adapted the interval type-2 fuzzy sets (IT2FSs) into QUALIFLEX as it reflects the uncertainty well in decision-making. IT2FQUALIFLEX algorithm under the Fine–Kinney concept provides a useful and solid approach to the occupational health and safety risk assessment. In addition to proposing this new approach, a case study is performed in the chrome plating unit. A validation is also performed in this study. Finally, the proposed approach is implemented in Python.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Vorheriges Kapitel Fine–Kinney-Based Occupational Risk Assessment Using Single-Valued Neutrosophic TOPSIS
Nächstes Kapitel Fine–Kinney-Based Occupational Risk Assessment Using Interval Type-2 Fuzzy VIKOR
Literatur
1.
Paelinck, J. H. P. (1976). Qualitative multiple criteria analysis, environmental protection and multiregional development. Papers of the Regional Science Association, 36, 59–74.CrossRef
2.
Alinezhad, A., & Khalili, J. (2019). QUALIFLEX method. In New methods and applications in multiple attribute decision making (MADM) (pp. 41–46). Springer, Cham.
3.
Chen, T. Y., Chang, C. H., & Lu, J. F. R. (2013). The extended QUALIFLEX method for multiple criteria decision analysis based on interval type-2 fuzzy sets and applications to medical decision making. European Journal of Operational Research, 226(3), 615–625.MathSciNetCrossRef
4.
Lee, L. W., Chen, S. M. (2008). Fuzzy multiple attributes group decision-making based on the extension of TOPSIS method and interval type-2 fuzzy sets. In Proceedings of the seventh international conference on machine learning and cybernetic (pp. 3260–3265). Taipei. Retrieved July 12–15, 2008.
5.
Chen, S. M., & Lee, L. W. (2010). Fuzzy multiple attributes group decision-making based on the interval type-2 TOPSIS method. Expert Systems with Applications, 37(4), 2790–2798.CrossRef
6.
Gul, M., Guven, B., & Guneri, A. F. (2018). A new Fine–Kinney-based risk assessment framework using FAHP-FVIKOR incorporation. Journal of Loss Prevention in the Process Industries, 53, 3–16.CrossRef
7.
Celik, E., Aydin, N., & Gumus, A. T. (2014). A multiattribute customer satisfaction evaluation approach for rail transit network: A real case study for Istanbul, Turkey. Transport Policy, 36, 283–293.CrossRef
8.
Wang, J. C., Tsao, C. Y., & Chen, T. Y. (2015). A likelihood-based QUALIFLEX method with interval type-2 fuzzy sets for multiple criteria decision analysis. Soft Computing, 19(8), 2225–2243.CrossRef
9.
Zhang, X. (2016). Multicriteria Pythagorean fuzzy decision analysis: A hierarchical QUALIFLEX approach with the closeness index-based ranking methods. Information Sciences, 330, 104–124.CrossRef
10.
Chen, T. Y. (2014). Interval-valued intuitionistic fuzzy QUALIFLEX method with a likelihood-based comparison approach for multiple criteria decision analysis. Information Sciences, 261, 149–169.MathSciNetCrossRef
11.
Li, J., & Wang, J. Q. (2017). An extended QUALIFLEX method under probability hesitant fuzzy environment for selecting green suppliers. International Journal of Fuzzy Systems, 19(6), 1866–1879.MathSciNetCrossRef
12.
Zhang, X., & Xu, Z. (2015). Hesitant fuzzy QUALIFLEX approach with a signed distance-based comparison method for multiple criteria decision analysis. Expert Systems with Applications, 42(2), 873–884.MathSciNetCrossRef
13.
Zhang, X., Xu, Z., & Liu, M. (2016). Hesitant trapezoidal fuzzy QUALIFLEX method and its application in the evaluation of green supply chain initiatives. Sustainability, 8(9), 952.CrossRef
14.
Chen, T. Y. (2013). Data construction process and QUALIFLEX-based method for multiple-criteria group decision making with interval-valued intuitionistic fuzzy sets. International Journal of Information Technology & Decision Making, 12(03), 425–467.CrossRef
15.
Demirel, H., Akyuz, E., Celik, E., & Alarcin, F. (2019). An interval type-2 fuzzy QUALIFLEX approach to measure performance effectiveness of ballast water treatment (BWT) system on-board ship. Ships and Offshore Structures, 14(7), 675–683.CrossRef
16.
Gumus, A. T., Aydin, N., Celik, E. (2014). Passenger satisfaction evaluation for rail transit lines in Istanbul using qualiflex approach based on interval type-2 trapezoidal fuzzy numbers. In CIE 2014—44th international conference on computers and industrial engineering and IMSS 2014—9th international symposium on intelligent manufacturing and service systems, joint international symposium on the social impacts of developments in information, manufacturing and service systems—proceedings (pp. 343–357). Istanbul, Turkey.
17.
Celik, E., Gul, M., Aydin, N., Gumus, A. T., & Guneri, A. F. (2015). A comprehensive review of multi criteria decision making approaches based on interval type-2 fuzzy sets. Knowledge-Based Systems, 85, 329–341.CrossRef
18.
Mendel, J. M., John, R. I., & Liu, F. L. (2006). Interval type-2 fuzzy logical systems made simple. IEEE Transactions on Fuzzy Systems, 14(6), 808–821.CrossRef
19.
Zhang, Z. (2017). Multi-criteria decision-making using interval-valued hesitant fuzzy QUALIFLEX methods based on a likelihood-based comparison approach. Neural Computing and Applications, 28(7), 1835–1854.CrossRef
Metadaten
Titel
Fine–Kinney-Based Occupational Risk Assessment Using Interval Type-2 Fuzzy QUALIFLEX
verfasst von
Assoc. Prof. Muhammet Gul
Assoc. Prof. Suleyman Mete
Assist. Prof. Faruk Serin
Assoc. Prof. Erkan Celik
Copyright-Jahr
2021
Buch
Fine–Kinney-Based Fuzzy Multi-criteria Occupational Risk Assessment

Print ISBN: 978-3-030-52147-9

Electronic ISBN: 978-3-030-52148-6

Copyright-Jahr: 2021

DOI
https://doi.org/10.1007/978-3-030-52148-6_8

Neuer Inhalt

    Bildnachweise