Multi-criteria group decision-making using an extended edas method with interval type-2 fuzzy sets

Simple item page
dc.contributor.authorGhorabaee, Mehdi Keshavarz
dc.contributor.authorAmiri, Maghsoud
dc.contributor.authorZavadskas, Edmundas Kazimieras
dc.contributor.authorTurskis, Zenonas
dc.contributor.otherEkonomická fakultacs
dc.date.accessioned2017-03-21
dc.date.available2017-03-21
dc.date.issued2017-03-15
dc.description.abstractMulti-criteria decision-making (MCDM) methods are very useful in the real-world decision-making problems. We are usually confronted with the decision-making process in an uncertain environment, and the fuzzy set theory is an efficient tool to handle this uncertainty. Interval type-2 fuzzy sets are one of the extensions of the fuzzy sets which are very flexible to model an uncertain environment. This study is related to MCDM problems within the context of interval type-2 fuzzy sets (IT2FSs). The evaluation based on distance from average solution (EDAS) method is a new and efficient MCDM method, and assessment of alternatives in this method is based on the distance of them from average solution with respect to all criteria. In the EDAS method, each alternative has positive and negative distances which are used to determine the appraisal score of it. In this research, we present an extended EDAS method, which is named EDAS-IT2FSs, for dealing with multi-criteria group decision-making problems with interval type-2 fuzzy sets. Basic concepts of interval type-2 fuzzy sets and the arithmetic operations of trapezoidal IT2FSs are used to develop the extended EDAS method. A numerical example of multi-criteria subcontractor evaluation problem is used to illustrate the process of using the extended EDAS method. The example involves eight subcontractors that need to be evaluated with respect to seven criteria. A comparison and a sensitivity analysis based on different sets of criteria weights are also performed to show the validity of the proposed method. The results of these analyses show the efficiency and stability of the extended EDAS method.en
dc.formattext
dc.format.extent48-68 s.cs
dc.identifier.doi10.15240/tul/001/2017-1-004
dc.identifier.eissn2336-5604
dc.identifier.issn1212-3609
dc.identifier.urihttps://dspace.tul.cz/handle/15240/19855
dc.language.isoen
dc.publisherTechnical university of Liberec, Czech Republicen
dc.publisherTechnická Univerzita v Libercics
dc.publisher.abbreviationTUL
dc.relation.isbasedonAbbasianjahromi, H., Rajaie, H., & Shakeri, E. (2013). A framework for subcontractor selection in the construction industry. Journal of Civil Engineering and Management, 19(2), 158-168. doi:10.3846/13923730.2012.743922.
dc.relation.isbasedonAliakbari Nouri, F., Khalili Esbouei, S., & Antucheviciene, J. (2015). A hybrid MCDM approach based on fuzzy ANP and fuzzy TOPSIS for technology selection. Informatica, 26(3), 369-388. doi:10.15388/Informatica.2015.53.
dc.relation.isbasedonBaležentis, T., & Zeng, S. (2013). Group multi-criteria decision making based upon interval-valued fuzzy numbers: An extension of the MULTIMOORA method. Expert Systems with Applications, 40(2), 543-550. doi:10.1016/j.eswa.2012.07.066.
dc.relation.isbasedonBalin, A., & Baraçli, H. (2015). A fuzzy multi-criteria decision making methodology based upon the interval type-2 fuzzy sets for evaluating renewable energy alternatives in Turkey. Technological and Economic Development of Economy. doi:10.3846/20294913.2015.1056276.
dc.relation.isbasedonCelik, 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(September), 329-341. doi:10.1016/j.knosys.2015.06.004.
dc.relation.isbasedonCelik, E., Gumus, A. T., & Alegoz, M. (2014). A trapezoidal type-2 fuzzy MCDM method to identify and evaluate critical success factors for humanitarian relief logistics management. Journal of Intelligent & Fuzzy Systems, 27(6), 2847-2855. doi:10.3233/IFS-141246.
dc.relation.isbasedonChakraborty, S., Zavadskas, E. K., & Antucheviciene, J. (2015). Applications of waspas method as a multi-criteria decision-making tool. Economic Computation and Economic Cybernetics Studies and Research, 49(1), 1-17.
dc.relation.isbasedonChen, S.-M., & Lee, L.-W. (2010). Fuzzy multiple attributes group decision-making based on the ranking values and the arithmetic operations of interval type-2 fuzzy sets. Expert Systems with Applications, 37(1), 824-833. doi:10.1016/j.eswa.2009.06.094.
dc.relation.isbasedonChen, S.-M., Yang, M.-W., Lee, L.-W., & Yang, S.-W. (2012). Fuzzy multiple attributes group decision-making based on ranking interval type-2 fuzzy sets. Expert Systems with Applications, 39(5), 5295-5308. doi:10.1016/j.eswa.2011.11.008.
dc.relation.isbasedonChen, T.-Y. (2015). Likelihoods of interval type-2 trapezoidal fuzzy preference relations and their application to multiple criteria decision analysis. Information Sciences, 295, 303-322. doi:10.1016/j.ins.2014.10.007.
dc.relation.isbasedonEcer, F. (2015). Performance evaluation of internet banking branches via a hybrid MCDM model under fuzzy environment. Economic Computation & Economic Cybernetics Studies & Research, 49(2), 200-218.
dc.relation.isbasedonFaraji Sabokbar, H., Hosseini, A., Banaitis, A., & Banaitiene, N. (2016). A novel sorting method TOPSIS-SORT: an applicaiton for Tehran environmental quality evaluation. E&M Ekonomie a Management, 19(2), 87-104. doi:10.15240/tul/001/2016-2-006.
dc.relation.isbasedonHu, J., Zhang, Y., Chen, X., & Liu, Y. (2013). Multi-criteria decision making method based on possibility degree of interval type-2 fuzzy number. Knowledge-Based Systems, 43(May), 21-29. doi:10.1016/j.knosys.2012.11.007.
dc.relation.isbasedonKarabasevic, D., Zavadskas, E. K., Turskis, Z., & Stanujkic, D. (2016). The framework for the selection of personnel based on the SWARA and ARAS methods under uncertainties. Informatica, 27(1), 49-65. doi:10.15388/Informatica.2016.76.
dc.relation.isbasedonKeshavarz Ghorabaee, M., Amiri, M., Salehi Sadaghiani, J., & Hassani Goodarzi, G. (2014). Multiple criteria group decision-making for supplier selection based on COPRAS method with interval type-2 fuzzy sets. The International Journal of Advanced Manufacturing Technology, 75(5-8), 1115-1130. doi:10.1007/s00170-014-6142-7.
dc.relation.isbasedonKeshavarz Ghorabaee, M., Amiri, M., Sadaghiani, J. S., & Zavadskas, E. K. (2015a). Multi-criteria project selection using an extended VIKOR method with interval type-2 fuzzy sets. International Journal of Information Technology & Decision Making, 14(5), 993-1016. doi:10.1142/S0219622015500212.
dc.relation.isbasedonKeshavarz Ghorabaee, M., Zavadskas, E. K., Olfat, L., & Turskis, Z. (2015b). Multi-criteria inventory classification using a new method of evaluation based on distance from average solution (EDAS). Informatica, 26(3), 435-451. doi:10.15388/Informatica.2015.57.
dc.relation.isbasedonKeshavarz Ghorabaee, M., Zavadskas, E. K., Amiri, M., & Antucheviciene, J. (2016a). A new method of assessment based on fuzzy ranking and aggregated weights (AFRAW) for MCDM problems under type-2 fuzzy environment. Economic Computation and Economic Cybernetics Studies and Research, 50(1), 39-68.
dc.relation.isbasedonKeshavarz Ghorabaee, M., Zavadskas, E. K., Amiri, M., & Esmaeili, A. (2016b). Multi-criteria evaluation of green suppliers using an extended WASPAS method with interval type-2 fuzzy sets. Journal of Cleaner Production, 137, 213-229. doi:10.1016/j.jclepro.2016.07.031.
dc.relation.isbasedonKeshavarz Ghorabaee, M., Zavadskas, E. K., Amiri, M., & Turskis, Z. (2016c). Extended EDAS Method for Fuzzy Multi-criteria Decision-making: An Application to Supplier Selection. International Journal of Computers Communications & Control, 11(3), 358-371. doi:10.15837/ijccc.2016.3.2557.
dc.relation.isbasedonLazauskas, M., Zavadskas, E. K., & Šaparauskas, J. (2015). Ranking of priorities among the baltic capital cities for the development of sustainable construction. E&M Ekonomie a Management, 18(2), 15-24. doi:10.15240/tul/001/2015-2-002.
dc.relation.isbasedonLi, G., Kou, G., & Peng, Y. (2015). Dynamic fuzzy multiple criteria decision making for performance evaluation. Technological and Economic Development of Economy, 21(5), 705-719. doi:10.3846/20294913.2015.1056280.
dc.relation.isbasedonMahdiraji, H. A., Hajiagha, S. H. R., Hashemi, S. S., & Zavadskas, E. K. (2016). A grey multi-objective linear model to find critical path of a project by using time, cost, quality and risk parameters. E&M Ekonomie a Management, 19(1), 49-61. doi:10.15240/tul/001/2016-1-004.
dc.relation.isbasedonMardani, A., Jusoh, A., & Zavadskas, E. K. (2015). Fuzzy multiple criteria decision-making techniques and applications – Two decades review from 1994 to 2014. Expert Systems with Applications, 42(8), 4126-4148. doi:10.1016/j.eswa.2015.01.003.
dc.relation.isbasedonMardani, A., Jusoh, A., Zavadskas, E. K., Kazemilari, M., Ungku, N. U. A., & Khalifah, Z. (2016). Application of Multiple Criteria Decision Making Techniques in Tourism and Hospitality Industry: a Systematic Review. Transformations in Business & Economics, 15(1), 192-213.
dc.relation.isbasedonMendel, J. M., John, R. I., & Feilong, L. (2006). Interval Type-2 Fuzzy Logic Systems Made Simple. Fuzzy Systems, IEEE Transactions on Fuzzy Systems, 14(6), 808-821. doi:10.1109/TFUZZ.2006.879986.
dc.relation.isbasedonPlebankiewicz, E. (2012). A fuzzy sets based contractor prequalification procedure. Automation in Construction, 22(March), 433-443. doi:10.1016/j.autcon.2011.11.003.
dc.relation.isbasedonRazavi Hajiagha, S. H., Mahdiraji, H. A., Hashemi, S. S., & Turskis, Z. (2015). Determining weights of fuzzy attributes for multi-attribute decision-making problems based on consensus of expert opinions. Technological and Economic Development of Economy, 21(5), 738-755. doi:10.3846/20294913.2015.1058301.
dc.relation.isbasedonSang, X., & Liu, X. (2016). An interval type-2 fuzzy sets-based TODIM method and its application to green supplier selection. Journal of the Operational Research Society, 67(5), 722-734. doi:10.1057/jors.2015.86.
dc.relation.isbasedonStanujkic, D., Zavadskas, E. K., & Tamošaitienė, J. (2015). An approach to measuring website quality in the rural tourism industry based on atanassov intuitionistic fuzzy sets. E&M Ekonomie a Management, 18(4), 184-199. doi:10.15240/tul/001/2015-4-013.
dc.relation.isbasedonTošenovský, F. (2015). Multicriteria decision-making weights and a compet itive product design. E&M Ekonomie a Management, 18(1), 84-94. doi:10.15240/tul/001/2015-1-007.
dc.relation.isbasedonTriantaphyllou, E. (2013). Multi-criteria Decision Making Methods: A Comparative Study. New York: Springer. doi:10.1007/978-1-4757-3157-6.
dc.relation.isbasedonVahdani, B., Mousavi, S. M., Hashemi, H., Mousakhani, M., & Tavakkoli-Moghaddam, R. (2013). A new compromise solution method for fuzzy group decision-making problems with an application to the contractor selection. Engineering Applications of Artificial Intelligence, 26(2), 779-788. doi:10.1016/j.engappai.2012.11.005.
dc.relation.isbasedonWang, W., Liu, X., & Qin, Y. (2012). Multi-attribute group decision making models under interval type-2 fuzzy environment. Knowledge-Based Systems, 30(June), 121-128. doi: 10.1016/j.knosys.2012.01.005.
dc.relation.isbasedonYu, L., Yang, Z., & Tang, L. (2016). Prediction-Based Multi-Objective Optimization for Oil Purchasing and Distribution with the NSGA-II Algorithm. International Journal of Information Technology & Decision Making, 15(2), 423-451. doi:10.1142/S0219622016500097.
dc.relation.isbasedonZadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338-353. doi:10.1016/S0019-9958(65)90241-X.
dc.relation.isbasedonZadeh, L. A. (1975). The concept of a linguistic variable and its application to approximate reasoning—I. Information Sciences, 8(3), 199-249. doi:10.1016/0020-0255(75)90036-5.
dc.relation.isbasedonZavadskas, E. K., Turskis, Z., & Kildienė, S. (2014). State of art surveys of overviews on MCDM/MADM methods. Technological and Economic Development of Economy, 20(1), 165-179. doi:10.3846/20294913.2014.892037.
dc.relation.ispartofEkonomie a Managementcs
dc.relation.ispartofEconomics and Managementen
dc.relation.isrefereedtrue
dc.rightsCC BY-NC
dc.subjectmulti-criteria decision-makingen
dc.subjectinterval type-2 fuzzy setsen
dc.subjectfuzzy MCDMen
dc.subjectEDAS methoden
dc.subject.classificationC02
dc.subject.classificationC44
dc.subject.classificationC61
dc.subject.classificationC63
dc.subject.classificationL7
dc.titleMulti-criteria group decision-making using an extended edas method with interval type-2 fuzzy setsen
dc.typeArticleen
local.accessopen
local.citation.epage68
local.citation.spage48
local.facultyFaculty of Economics
local.fulltextyes
local.relation.abbreviationE+Mcs
local.relation.abbreviationE&Men
local.relation.issue1
local.relation.volume20
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
EM_1_2017_04.pdf
Size:
1.96 MB
Format:
Adobe Portable Document Format
Description:
článek
Download
Collections
Číslo 1