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A Novel Method for Measuring the Performance of Decision Alternatives in Multi-Criteria Decision Making: Proportional Superiority Approach (PSA)

Yıl 2024, Cilt: 5 Sayı: 2, 102 - 126
https://doi.org/10.53525/jster.1501506

Öz

In the face of increasing complexity and uncertainty, new multi-criteria decision making (MCDM) methods facilitate making informed and rational decisions by enhancing problem-solving skills. Therefore, the discovery of new MCDM methods is of great importance. In this context, this study introduces a new MCDM model (Proportional Superiority Approach-PSA) based on the fundamental logic of measuring the performance of decision alternatives, which relies on the proportional increase of decision alternatives to each other, aiming to expand the modeling logic of MCDM and enrich MCDM literature. Initially, a comparative analysis of the proposed method was conducted. According to the findings, although the relationship of PSA with other MCDM methods included in the study was high, it was found to be different from those MCDM methods. Therefore, based on the results of the comparative analysis, it was observed that the proposed method is credible and reliable. In the scope of the simulation analysis, 10 scenarios were obtained, and it was found that as the number of scenarios increased, the relationship levels of the PSA method with other methods differed and decreased. Furthermore, the PSA method was found to be capable of discriminating between the performances of decision alternatives through variance measurement. Finally, in the analysis, the level of variance of the PSA method was measured within the scenarios, and it was found that the variances of the PSA method were homogeneous within the scenarios. Therefore, according to the results of the simulation analysis, it was evaluated that the PSA method is robust and stable.

Kaynakça

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Çok Kriterli Karar Verme Kapsamında Karar Alternatiflerin Performanslarının Ölçümüne Yönelik Yeni Bir Yaklaşım: Oransal Üstünlük Yaklaşaımı

Yıl 2024, Cilt: 5 Sayı: 2, 102 - 126
https://doi.org/10.53525/jster.1501506

Öz

Artan karmaşıklık ve belirsizlik karşısında, yeni çok kriterli karar verme (ÇKKV) yöntemleri, problem çözme becerilerini geliştirerek bilgilendirilmiş ve rasyonel kararlar alınmasını kolaylaştırır. Bu nedenle, yeni ÇKKV yöntemlerinin keşfi büyük önem taşımaktadır. Bu bağlamda, bu çalışma, karar alternatiflerinin performansını ölçmenin temel mantığına dayanan ve ÇKKV modelleme mantığını genişletmeyi ve ÇKKV literatürünü zenginleştirmeyi amaçlayan yeni bir ÇKKV modeli (Orantılı Üstünlük Yaklaşımı-PSA) sunmaktadır. Öncelikle, önerilen yönteminin karşılaştırmalı bir analizi yapılmıştır. Bulgulara göre, PSA'nın çalışmaya dahil edilen diğer ÇKKV yöntemleriyle ilişkisi yüksek olmasına rağmen, bu ÇKKV yöntemlerinden farklı olduğu bulunmuştur. Dolayısıyla, karşılaştırmalı analiz sonuçlarına dayanarak, önerilen yöntemin güvenilir ve geçerli olduğu gözlemlenmiştir. Simülasyon analizinin kapsamında, 10 senaryo elde edilmiş ve senaryo sayısı arttıkça, PSA yönteminin diğer yöntemlerle olan ilişki seviyelerinin farklılaştığı ve azaldığı bulunmuştur. Ayrıca, PSA yönteminin, varyans ölçümü yoluyla karar alternatiflerinin performansları arasında ayrım yapabildiği tespit edilmiştir. Son olarak, analizde, PSA yönteminin senaryolar içindeki varyans seviyesi ölçülmüş ve PSA yönteminin varyanslarının senaryolar içinde homojen olduğu bulunmuştur. Dolayısıyla, simülasyon analizinin sonuçlarına göre, PSA yönteminin sağlam ve istikrarlı olduğu değerlendirilmiştir.

Kaynakça

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  • [2] Al Khoiry, I., & Amelia, D. R. (2023). Exploring simple addictive weighting (SAW) for decision making. Jurnal Inovtek Polbeng - Seri Informatika, 8(2), 281-290. DOI: 10.35314/isi.v8i2.3433.
  • [3] Amor, S. B., De Almedia, A. T., De Miranda, J. L., & Aktas, E. (2021). Advanced studies in multi-criteria decision making. Oxfordshire: Taylor & Francis.
  • [4] Atan, M., & Altan, Ş. (2020). Örnek uygulamalarla çok kriterli karar verme yöntemleri. Ankara: Gazi Kitapevi.
  • [5] Ayçin, E. (2019). Çok kriterli karar verme . Ankara: Nobel Yayın.
  • [6] Azad, T. (2019). Implementation of TOPSIS method for multi criteria decision making of supplier selection. European Journal of Advances in Engineering and Technology, 6(11), 22-27.
  • [7] Behl, A. (2020). Multi-Criteria Decision Analysis in Management. Hershey, PA : Business Science Reference.
  • [8] Biswas, T. K., Chaki, S., & Das, M. C. (2019). MCDM technique application to the selection of an Indian institute of technology. Operational Research in Engineering Sciences: Theory and Applications, 2(3), 65-76. DOI: 10.31181/ 10.31181/oresta1903065b.
  • [9] Bridgman, P. W. (1922). Dimensional analysis. New Haven: Yale University Press.
  • [10] Chinnasamy, S., Ramachandran, M., Rajkumar, S., & Sivaji, C. (2023). A survey on transportation system using the WPM method. Building Materials and Engineering Structures, 1(2), 37-44. DOI: 10.46632/bmes/1/2/5.
  • [11] Chourabi, Z., Khedher, F., Babay, A., & Cheikhrouhou, M. (2019). Multi criteria decision making in workforce choice using AHP, WSM and WPM. The Journal of The Textile Institute, 110(7), 1092-1101. DOI: 10.1080/00405000.2018.1541434.
  • [12] Churchman, C. W., & Ackoff, R. L. (1954). An approximate measure of value. Journal of Operationn Research Society of America, 2(2), 172-187.
  • [13] Ciardiello, F., & Genovese, A. (2023). A comparison between TOPSIS and SAW methods. Annals of Operations Research, 325, 967–994. DOI: 10.1007/s10479-023-05339-w.
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  • [15] Demir, G., Özyalçın, A. T., & Bircan, H. (2021). Çok kriterli karar verme yöntemleri ve ÇKKV yazılımı ile problem çözümü. Ankara: Nobel.
  • [16] Demirci, A. (2020). Sağlık hizmetleri yönetiminde çok kriterli karar verme teknikleri. Ankara: Gazi Kitapevi.
  • [17] Dhanalakshmi, C. S., Madhu, P., Karthick, A., Mathew, M., & Kumar, R. V. (2022). A comprehensive MCDM-based approach using TOPSIS and EDAS as an auxiliary tool for pyrolysis material selection and its application. Biomass Conv. Bioref, 12, s. 5845–5860. DOI: 10.1007/s13399-020-01009-0.
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  • [19] Ecer, F. (2020). Çok kriterli karar verme. Ankara: Seçkin Yayıncılık.
  • [20] Ghorabaee, M. K., Zavadskas, E. K., Olfat, L., & Turskis, Z. (2015). Multi criteria inventory classification using a new method of evaluation based on distance from avarege solution (EDAS). Informatica, 26(3), 435-451. DOI: 10.15388/Informatica.2015.57
  • [21] Goswami, S. S., & Behera, D. K. (2021). Solving material handling equipment selection problems in an industry with the help of Entropy integrated COPRAS and ARAS MCDM techniques. Process Integr. Optim. Sustain., 5, 947–973. DOI: 10.1007/s41660-021-00192-5.
  • [22] Handayani, N., Heriyani, N., Septian, F., & Alexander, A. D. (2023). Multi-criteria decision making using The WASPAS method for online English course selection. Jurnal Teknoinfo, 17(1), 260-270.
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  • [24] Hezer, S., Gelmez, E., & Özceylan, E. (2021). Comparative analysis of TOPSIS, VIKOR and COPRAS methods for the COVID 19 regional safety assessment. Journal of Infection and Public Health, 14, 775–786. DOI: 10.1016/j.jiph.2021.03.003
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  • [26] Kabir, G., & Hasin, M. A. (2012). Comparative analysis of TOPSIS and FUZZY TOPSIS for the evaluation of travel website service quality. International Journal for Quality Research, 6(3), 169-185.
  • [27] Karabašević, D., Stanujkić, D., & Urošević, S. (2015). The MCDM model for personnel selection based on SWARA and ARAS methods. Management, 77, 43-51.
  • [28] Karakış, E. (2021). Machine selection for a textile company with CRITIC and MAUT methods. Avrupa Bilim ve Teknoloji Dergisi(27), 842-848. DOI: 10.31590/ejosat.994697
  • [29] Karande, P., Zavadskas, E. K., & Chakraborty, S. (2016). A study on the ranking performance of some MCDM methods for industrial robot selection problems. International Journal of Industrial Engineering Computations, 7(3), 399-422. DOI: 10.5267/j.ijiec.2016.1.001
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  • [32] Keshavarz-Ghorabaee, M., Amiri, M., Zavadskas, E. K., Turskis, Z., & Antucheviciene, J. (2021). Determination of objective weights using a new method based on the removal effects of criteria (MEREC). Symmetry, 13, 1-20. DOI: 10.3390/sym13040525
  • [33] Lopez, L. M., Ishizaka, A., & Qin, J. (2023). Multi criteria decision making sorting methods: applications to real world. Cambridge-Massachusetts: Academic Press.
  • [34] Maharani, S., Ridwanto, H., Hatta, H. R., Khairina, D. M., & Ibrahim, M. R. (2021). Comparison of TOPSIS and MAUT methods for recipient determination home surgery. IAES International Journal of Artificial Intelligence (IJ-AI), 10(4), 930~937. DOI: 10.11591/ijai.v10.i4.pp930-937.
  • [35] Maniya, K., & Bhatt, M. G. (2010). A selection of material using a novel type decision-making method: Preference selection index method. Materials and Design(31), 1785-1789.
  • [36] Mousavi-Nasab, S. H., & Sotoudeh-Anvari, A. (2017). A comprehensive MCDM based approach using TOPSIS, COPRAS and DEA as an auxiliary tool for material selection problems. Materials & Design, 121, 237-253. DOI: 10.1016/j.matdes.2017.02.041
  • [37] Onajite, O., & Oke, S. A. (2021). The application of WSM, WPM and WASPAS multicriteria methods for optimum operating conditions selection in machining operations. Jurnal Rekayasa Sistem Industri, 10(1), 1-15. DOI: 10.26593/jrsi.v10i1.4271.1-14.
  • [38] Özbek, A. (2019). Çok kriterli karar verme yöntemleri ve excel ile problem çözümü kavram-teori-uygulama (2. b.). Ankara: Seçkin Yayıncılık.
  • [39] Öztel, A., & Alp, İ. (2020). Çok kriterli karar verme yöntemi seçiminde yeni bir yaklaşim. İstanbul: Kriter Yayınevi.
  • [40] Paksoy, S. (2017). Çok kriterli karar vermede güncel yaklaşimlar. Adana: Karahan Kitapevi.
  • [41] Petković, D., Madić, M., Radovanović, M., & Gečevska, V. (2017). Application of the performance selection index method for solving machining MCDM problems. FACTA Universitatis-Series: Mechanical Engineering, 15(1), 97-106. DOI: 10.22190/FUME151120001P.
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  • [46] Taherdoost, H. (2023). Analysis of Simple Additive Weighting Method (SAW) as a Multi-Attribute Decision-Making Technique: A Step-by-Step Guide. Journal of Management Science & Engineering Research, 6(1), 21-24. DOI: 10.30564/jmser.v6i1.5400
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Toplam 64 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Çok Ölçütlü Karar Verme
Bölüm Araştırma Makaleleri
Yazarlar

Furkan Fahri Altıntaş 0000-0002-0161-5862

Yayımlanma Tarihi
Gönderilme Tarihi 14 Haziran 2024
Kabul Tarihi 6 Ağustos 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 5 Sayı: 2

Kaynak Göster

APA Altıntaş, F. F. (t.y.). A Novel Method for Measuring the Performance of Decision Alternatives in Multi-Criteria Decision Making: Proportional Superiority Approach (PSA). Journal of Science, Technology and Engineering Research, 5(2), 102-126. https://doi.org/10.53525/jster.1501506
AMA Altıntaş FF. A Novel Method for Measuring the Performance of Decision Alternatives in Multi-Criteria Decision Making: Proportional Superiority Approach (PSA). JSTER. 5(2):102-126. doi:10.53525/jster.1501506
Chicago Altıntaş, Furkan Fahri. “A Novel Method for Measuring the Performance of Decision Alternatives in Multi-Criteria Decision Making: Proportional Superiority Approach (PSA)”. Journal of Science, Technology and Engineering Research 5, sy. 2 t.y.: 102-26. https://doi.org/10.53525/jster.1501506.
EndNote Altıntaş FF A Novel Method for Measuring the Performance of Decision Alternatives in Multi-Criteria Decision Making: Proportional Superiority Approach (PSA). Journal of Science, Technology and Engineering Research 5 2 102–126.
IEEE F. F. Altıntaş, “A Novel Method for Measuring the Performance of Decision Alternatives in Multi-Criteria Decision Making: Proportional Superiority Approach (PSA)”, JSTER, c. 5, sy. 2, ss. 102–126, doi: 10.53525/jster.1501506.
ISNAD Altıntaş, Furkan Fahri. “A Novel Method for Measuring the Performance of Decision Alternatives in Multi-Criteria Decision Making: Proportional Superiority Approach (PSA)”. Journal of Science, Technology and Engineering Research 5/2 (t.y.), 102-126. https://doi.org/10.53525/jster.1501506.
JAMA Altıntaş FF. A Novel Method for Measuring the Performance of Decision Alternatives in Multi-Criteria Decision Making: Proportional Superiority Approach (PSA). JSTER.;5:102–126.
MLA Altıntaş, Furkan Fahri. “A Novel Method for Measuring the Performance of Decision Alternatives in Multi-Criteria Decision Making: Proportional Superiority Approach (PSA)”. Journal of Science, Technology and Engineering Research, c. 5, sy. 2, ss. 102-26, doi:10.53525/jster.1501506.
Vancouver Altıntaş FF. A Novel Method for Measuring the Performance of Decision Alternatives in Multi-Criteria Decision Making: Proportional Superiority Approach (PSA). JSTER. 5(2):102-26.
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