A Hybrid Moora-Fuzzy Algorithm For Special Education and Rehabilitation Center Selection

Year 2014, Volume: 2 Issue: 3, 53 - 62, 21.09.2014

Gökhan Ozcelik , Emel Aydoğan , Cevriye Gencer

https://doi.org/10.17858/jmisci.53708

Cited By: 9

Abstract

Special education and rehabilitation centers are established in order to train children and young people who need
special education. The main goal of this study is to determine the most appropriate special education and rehabilitation center, in terms of various criteria by evaluating three different corporations which are active in Kayseri/Turkey. For that purpose, we apply Fuzzy Analytic Hierarchy Process and MOORA which are the methods of multi-criteria decision making. Education, compliance of ergonomic, compliance of corporation building, cost, public opinion and prestige and assessment of personnel are considered as the criteria. Firstly, these criteria are weighted by using Fuzzy Analytic Hierarchy Process, later MOORA method is used to choose the most appropriate corporation.

Keywords

Special Education and Rehabilitation Center; MOORA; Fuzzy Analytic Hierarchy Process; Multi Criteria Decision Making.

References

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• The International Journal of Advanced Manufacturing Technology, 49(5-8), 785-801. APPENDIX A Table 10. Pairwise comparison matrix and fuzzy weights for criteria Pairwise comparison matrix and fuzzy weights for criteria Criteria ED ER IB CO IP AP Education (ED) (1, 1, 1) (1, 2, 4) (5, 7, 9) (3, 5, 7) (1/7, 1/5, 1/3) (3, 5, 7) Ergonomics (ER) (1/4, 1/2, 1) (1, 1, 1) (1, 1, 1) (3, 5, 7) (1, 2, 4) (1, 2, 4) Institution’s Building (IB) (1/9, 1/7, 1/5) (1, 1, 1) (1, 1, 1) (1/4, 1/2, 1) (1/7, 1/5, 1/3) (1/4, 1/2, 1) Cost (CO) (1/7, 1/5, 1/3) (1/7, 1/5, 1/3) (1, 2, 4) (1, 1, 1) (1, 2, 4) (1/7, 1/5, 1/3) Image and Prestige (IP) (3, 5, 7) (1/4, 1/2, 1) (3, 5, 7) (1/4, 1/2, 1) (1, 1, 1) (5, 7, 9) Assessment of Personnel (AP) (1/7, 1/5, 1/3) (1/4, 1/2, 1) (1, 2, 4) (3, 5, 7) (1/9, 1/7, 1/5) (1, 1, 1) Geometric mean of the 1 th row: 1/6 1/6 1/6 {(1×1×5×3×1/7×3) ,(1×2×7×5×1/5×5) ,(1×4×9×7x1/3×7) }=(36, 2.03, 2.89) Geometric mean of the 2nd row: 1/6 1/6 1/6 {(1/4×1×1×3×1×1) ,(1/2×1×1×5×2×2) ,(1×1×1×7×4×4) }=(0.95, 1.47, 2.20) Geometric mean of the 3 rd row: 1/6 1/6 1/6 {(1/9×1×1×1/4×1/7×1/4) ,(1/7×1×1×1/2×1/5×1/2) ,(1/5×1×1×1×1/3×1) }=(0.31, 0.44, 0.64) Geometric mean of the 4 th row: 1/6 1/6 1/6 {(1/7×1/7×1×1×1×1/7) ,(1/5×1/5×2×1×2×1/5) ,(1/3×1/3×4×1×4×1/3) }=(0.38, 0.56, 0.92) Geometric mean of the 5 th row: 1/6 1/6 1/6 {(3×1/4×3×1/4×1×5) ,(5×1/2×5×1/2×1×7) ,(7×1×7×1×1×9) }=(19, 1.88, 2.76) Geometric mean of the 6 th row: 1/6 1/6 1/6 {(1/7×1/4×1×3×1/9×1) ,(1/5×1/2×2×5×1/7×1) ,(1/3×1×4×7×1/5×1) }=(0.48, 0.72, 1.11) The sum of the fuzzy geometric averages: (4.67, 7.1, 10.52) The fuzzy weight of ED Factor: {(1.36/10.52, 2.03/7.1, 2.89/4.67)}=(0.13, 0.29, 0.62) The fuzzy weight of ER Factor: {(0.95/10.52, 1.47/7.1, 2.20/4.67)}= (0.09, 0.21, 0.47) The fuzzy weight of IB Factor: {(0.31/10.52, 0.44/7.1, 0.64/4.67)}=(0.03, 0.06, 0.14) The fuzzy weight of CO Factor: {(0.38/10.52, 0.56/7.1, 0.92/4.67)}=(0.04, 0.08, 0.20) The fuzzy weight of IP Factor: {(1.19/10.52, 1.88/7.1, 2.76/4.67)}=(0.11, 0.26, 0.59) The fuzzy weight of AP Factor: {(0.48/10.52, 0.72/7.1, 1.11/4.67)}= (0.05, 0.10, 0.24)