Tuesday , December 18 2018

An Extension of the EDAS Method Based on the Use of Interval Grey Numbers

Dragisa Stanujkic1, Edmundas Kazimieras Zavadskas2,
Mehdi KESHAVARZ Ghorabaee3, Zenonas Turskis4  

1 Faculty of Management Zajecar, John Naisbitt University
Park suma Kraljevica b.b., Zajecar 19210, Serbia.
dragisa.stanujkic@fmz.edu.rs
2 Research Institute of Smart Building Technologies,
Vilnius Gediminas Technical University

Saulėtekio al. 11, Vilnius 10221, Lithuania.
edmundas.zavadskas@vgtu.lt

3 Faculty of Management and Accounting, Allameh Tabataba’i University
Dehkadeh-ye-Olympic, Tehran, Tehran Province, Iran
m.keshavarz_gh@yahoo.com
4 Faculty of Civil Engineering, Vilnius Gediminas Technical University
Saulėtekio al. 11, Vilnius 10221, Lithuania
zenonas.turskis@vgtu.lt

ABSTRACT: In order to solve a number of real decision-making problems, over time, a number of multiple criteria decision-making methods have been proposed. The EDAS method is one of the newly proposed methods; its computational procedure can be identified as innovative and also based on verified approaches. An extension of the EDAS method adapted for the use of grey numbers is considered in this paper.

KEYWORDS: EDAS, MCDM, uncertainty, grey systems, interval grey numbers.

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CITE THIS PAPER AS:
Dragisa Stanujkic, Edmundas Kazimieras Zavadskas, Mehdi KESHAVARZ Ghorabaee, Zenonas Turskis, An Extension of the EDAS Method Based on the Use of Interval Grey Numbers
, Studies in Informatics and Control, ISSN 1220-1766, vol. 26(1), pp. 5-12, 2017. https://doi.org/10.24846/v26i1y201701

REFERENCES

  1. Baradaran, V., & Azarnia, S. (2013). An Approach to Test Consistency and Generate Weights from Grey Pairwise Matrices in Grey Analytical Hierarchy Process. Journal of Grey System, 25 (2), 46-68.
  2. Chatterjee, P., & Chakraborty, S. (2012). Material selection using preferential ranking methods. Materials & Design, 35, 384-393.
  3. Chen, M. F., & Tzeng, G. H. (2004). Combining grey relation and TOPSIS concepts for selecting an expatriate host country. Mathematical and Computer Modelling, 40 (13), 1473-1490.
  4. Chen, T. Y. (2012). Comparative analysis of SAW and TOPSIS based on interval-valued fuzzy sets: Discussions on score functions and weight constraints. Expert Systems with Applications, 39 (2), 1848-1861.
  5. Datta, S., Sahu, N., & Mahapatra, S. (2013). Robot selection based on grey-MULTIMOORA approach. Grey Systems: Theory and Application, 3 (2), 201-232.
  6. Deng, J. L. (1982). Control problems of grey systems. Systems & Control Letters, 1 (5), 288-294.
  7. Deng, J. L. (1989). Introduction to grey system theory. The Journal of grey system, 1 (1), 1-24.
  8. Deng, J. L. (1992). An Introduction to Grey Mathematics–Grey Hazy Set. Press of Huazhong University of Science and Technology, Wuhan.
  9. Ghadikolaei, A. S., Esbouei, S. K., & Antucheviciene, J. (2014). Applying fuzzy MCDM for financial performance evaluation of Iranian companies. Technological and Economic Development of Economy, 20 (2), 274-291.
  10. Ghosh, S., Chakraborty, T., Saha, S., Majumder, M., & Pal, M. (2016). Development of the location suitability index for wave energy production by ANN and MCDM techniques. Renewable and Sustainable Energy Reviews, 59, 1017-1028.
  11. Hashemkhani Zolfani, S., & Antucheviciene, J. (2012). Team member selecting based on AHP and TOPSIS grey. Inzinerine Ekonomika-Engineering Economics, 23 (4), 424-434.
  12. Hashemkhani Zolfani, S., Rezaeiniya, N., & Saparauskas, J. (2012). Selecting the best multi-role artist of rock bands of Iran 2000s by applying ANP and TOPSIS grey. Economic Computation and Economic Cybernetics Studies and Research, 46 (2), 193-211.
  13. Hwang, C. L., & Yoon, K. (1981). Multiple attribute decision making: methods and applications. Springer, New York.
  14. Kaliszewski, I., & Podkopaev, D. (2016). Simple additive weighting – A metamodel for multiple criteria decision analysis methods. Expert Systems with Applications, 54 (15), 155-161.
  15. Keshavarz Ghorabaee, M., Zavadskas, E. K., Amiri, M., & Turskis, Z. (2016). Extended EDAS method for fuzzy multi-criteria decision-making: an application to supplier selection. International Journal of Computers Communications & Control, 11 (3), 358-371.
  16. Keshavarz Ghorabaee, M., Zavadskas, E. K., Olfat, L., & Turskis, Z. (2015). Multi-criteria inventory classification using a new method of evaluation based on distance from average solution (EDAS). Informatica, 26 (3), 435-451.
  17. Kou, G., Lu, Y., Peng, Y., & Shi, Y. (2012). Evaluation of classification algorithms using MCDM and rank correlation. International Journal of Information Technology & Decision Making, 11 (01), 197-225.
  18. Kumar Sahu, A., Datta, S., & Sankar Mahapatra, S. (2014). Supply chain performance benchmarking using grey-MOORA approach: An empirical research. Grey Systems: Theory and Application, 4 (1), 24-55.
  19. Leonaviciute, G., Dejus, T., & Antucheviciene, J. (2016). Analysis and prevention of construction site accidents. Gradevinar, 68 (05), 399-410.
  1. Li, M., Jin, L., & Wang, J. (2014). A new MCDM method combining QFD with TOPSIS for knowledge management system selection from the user’s perspective in intuitionistic fuzzy environment. Applied soft computing, 21, 28-37.
  2. Lin, Y. H., Lee, P. C., Chang, T. P., & Ting, H. I. (2008). Multi-attribute group decision making model under the condition of uncertain information. Automation in Construction, 17 (6), 792-797.
  3. Liou, J. J., Tamosaitiene, J., Zavadskas, E. K., & Tzeng, G. H. (2016). New hybrid COPRAS-G MADM Model for improving and selecting suppliers in green supply chain management. International Journal of Production Research, 54 (1), 114-134.
  4. Liu, S. F., & Lin, Y. (2006). Grey information: theory and practical applications. Springer Science & Business Media.
  5. MacCrimmon, K. R. (1968). Decisionmaking among multiple-attribute alternatives: a survey and consolidated approach (No. RM-4823-ARPA), RAND memorandum.
  6. Mardani, A., Jusoh, A., Zavadskas, E. K., Zakuan, N., Valipour, A., & Kazemilari, M. (2016). Proposing a new hierarchical framework for the evaluation of quality management practices: a new combined fuzzy hybrid MCDM approach. Journal of Business Economics and Management, 17 (1), 1-16.
  7. Marzouk, M., & Awad, E. (2016). Establishing Multi-level Performance Condition Indices for Public Schools Maintenance Program Using AHP and Fuzzy Logic. Studies in Informatics and Control, 25 (3), 343-352.
  8. Mehrjerdi, Y. Z. (2014). Strategic system selection with linguistic preferences and grey information using MCDM. Applied Soft Computing, 18, 323-337.
  9. Opricovic, S. (1998). Visekriterijumska optimizacija u građevinarstvu [Multi-criteria optimization of civil engineering systems], Faculty of Civil Engineering, Belgrade.
  10. Pavlovskis, M., Antucheviciene, J., & Migilinskas, D. (2016). Application of MCDM and BIM for Evaluation of Asset Redevelopment Solutions. Studies in Informatics and Control, 25 (3), 293-302.
  11. Ren, J., Manzardo, A., Mazzi, A., Zuliani, F., & Scipioni, A. (2015). Prioritization of bioethanol production pathways in China based on life cycle sustainability assessment and multicriteria decision-making. The International Journal of Life Cycle Assessment, 20 (6), 842-853.
  12. Siozinyte, E., Antucheviciene, J., & Kutut, V. (2014). Upgrading the old vernacular building to contemporary norms: multiple criteria approach. Journal of Civil Engineering and Management, 20 (2), 291-298.
  13. Stanujkic, D., Magdalinovic, N., Stojanovic, S., & Jovanovic, R. (2012). Extension of ratio system part of MOORA method for solving decision-making problems with interval data. Informatica, 23 (1), 141-154.
  14. Tamosaitiene, J., & Gaudutis, E. (2013). Complex assessment of structural systems used for high-rise buildings. Journal of Civil Engineering and Management, 19 (2), 305-317.
  15. Tavana, M., Momeni, E., Rezaeiniya, N., Mirhedayatian, S. M., & Rezaeiniya, H. (2013). A novel hybrid social media platform selection model using fuzzy ANP and COPRAS-G. Expert Systems with Applications, 40 (14), 5694-5702.
  16. Turskis, Z., Daniunas, A., Zavadskas, E. K., & Medzvieckas, J. (2016). Multicriteria evaluation of building foundation alternatives. Computer-Aided Civil and Infrastructure Engineering, 31 (9), 717-729.
  17. Turskis, Z., & Zavadskas, E. K. (2010). A novel method for multiple criteria analysis: grey additive ratio assessment (ARAS-G) method. Informatica, 21 (4), 597-610.
  18. Yan, J., Xie, Z., Chen, K., & Lin, Y. (2015). Air traffic management system safety evaluation based on grey evidence theory. The Journal of Grey System, 27 (3), 23-39.
  19. Zavadskas, E. K., Kaklauskas, A., Turskis, Z., & Tamosaitiene, J. (2009). Multi-attribute decision-making model by applying grey numbers. Informatica, 20 (2), 305-320.
  20. Zavadskas, E. K., Kaklauskas, A., Turskis, Z., & Tamosaitiene, J. (2008). Selection of the effective dwelling house walls by applying attributes values determined at intervals. Journal of Civil Engineering and Management, 14 (2), 85-93.
  21. Zavadskas, E. K., Turskis, Z., & Antucheviciene, J. (2015). Selecting a Contractor by Using a Novel Method for Multiple Attribute Analysis: Weighted Aggregated Sum Product Assessment with Grey Values (WASPAS-G). Studies in Informatics and Control, 24 (2), 141-150.
  22. Zavadskas, E. K., Turskis, Z., Volvaciovas, R., & Kildiene, S. (2013). Multi-criteria assessment model of technologies. Studies in Informatics and Control, 22 (4), 249-258.