Pythagorean Fuzzy Analytical Network Process (ANP) and Its Application to Warehouse Location Selection Problem

• Autorzy: Yaman Tutku Tuncalı

Identyfikatory

DOI

10.15439/2020F187

• Konferencja: Federated Conference on Computer Science and Information Systems (15 ; 06-09.09.2020 ; Sofia, Bulgaria)
• Języki publikacji: EN

Abstrakty

EN

Although new techniques are added to multi-criteria decision-making (MCDM) techniques every day, fuzzy applications of current and proven methods also take a large place in the literature. The main subject of this study is to propose an extension of Pythagorean fuzzy sets (PFS), which are useful to overcome the uncertainty in multi-criteria decision processes, to the well-known Analytical Network Process (ANP) technique. For this purpose, an empirical application of the proposed method was carried out in defining criteria weights of the warehouse location selection problem in the medical sector.

Słowa kluczowe

EN

analytic hierarchy process; facility location; fuzzy set theory; operations research

PL

proces hierarchii analitycznej; lokalizacja obiektu; teoria zbiorów rozmytych; badania operacyjne

• Wydawca: Polskie Towarzystwo Informatyczne
• Czasopismo: Annals of Computer Science and Information Systems
• Rocznik: 2020
• Tom: Vol. 21
• Strony: 137--140
• Opis fizyczny: Bibliogr. 35 poz., tab.

Twórcy

autor

Yaman Tutku Tuncalı

• Beykent University Management Information, Systems Department Istanbul, Turkey

Bibliografia

• 1. L. Zadeh, “Fuzzy-set-theoretic interpretation of linguistic hedge”, Journal of Cybernetics, vol. 2, 1972, pp. 4–34. https://doi.org/10.1080/01969727208542910
• 2. L. Zadeh, “The concept of a linguistic variable and its application to approximate reasoning-1”, Information Sciences, 1975, pp. 199–249. https://doi.org/10.1016/0020-0255(75)90036-5
• 3. R.R. Yager, “A characterization of the extension principle,” Fuzzy Sets and Systems, vol. 18, no. 3, 1986, pp. 205–217. https://doi.org/10.1016/0165-0114(86)90002-3
• 4. K. Atanassov, “Intuitionistic fuzzy sets”, Fuzzy Sets and Systems, vol. 20, no.1, 1986, pp.87–96. https://doi.org/10.1016/S0165-0114(86)80034-3
• 5. E. Bolturk, “Pythagorean fuzzy CODAS and its application to supplier selection in a manufacturing firm”, Journal of Enterprise Information Management, vol.31, no.4, 2018, pp.550–564. https://doi.org/10.1108/JEIM-01-2018-0020
• 6. T. L. Saaty, Decisions with the analytic network process (ANP). University of Pittsburgh, USA: ISAHP, 1996.
• 7. S-L. Si, X-Y. You, H-C. Liu, and P. Zhang, “DEMATEL technique: a systematic review of the state-of-the-art literature on methodologies and applications.” Mathematical Problems in Engineering, vol. 2018, 2018, pp. 1-33. https://doi.org/10.1155/2018/3696457
• 8. M. Reisi, A. Afsaneh, and A. Lu,"Applications of analytical hierarchy process (AHP) and analytical network process (ANP) for industrial site selections in Isfahan, Iran." Environmental Earth Sciences, vol.77, no. 537, 2018, pp.1-13. https://doi.org/10.1007/s12665-018-7702-1
• 9. E. Ilbahar, A. Karaşan, S. Cebi, and C. Kahraman, “A novel approach to risk assessment for occupational health and safety using Pythagorean fuzzy AHP & fuzzy inference system”, Safety Science, vol. 103, 2018, pp. 124-136. https://doi.org/10.1016/j.ssci.2017.10.025
• 10. J. Korpela, and M. Tuominen, "A decision aid in warehouse site selection." International Journal of Production Economics, vol. 45. no.1-3, 1996, pp. 169-180. https://doi.org/10.1016/0925-5273(95)00135-2
• 11. C. Boonmee, Chawis, and C. Kasemset. "The Multi-Objective Fuzzy Mathematical Programming Model for Humanitarian Relief Logistics." Industrial Engineering & Management Systems, vol. 19, no.1, pp.197-210, 2020. https://doi.org/10.7232/iems.2020.19.1.197
• 12. F. Kutlu Gündoğdu, and C. Kahraman, Spherical Fuzzy Sets and Decision Making Applications. In: International Conference on Intelligent and Fuzzy Systems. Springer, Cham, 2019, pp. 979-987. https://doi.org/10.1007/978-3-030-23756-1_116
• 13. M. Khaengkhan, C. Hotrawisaya, B. Kiranantawat, and M. R. Shaharudin, “Comparative analysis of multiple criteria decision making (MCDM) approach in warehouse location selection of agricultural products in Thailand”, International Journal of Supply Chain Management, vol. 8, no. 5, pp. 168-175, 2019.
• 14. I. Otay, and M. Jaller. "Multi-criteria and multi-expert wind power farm location selection using a pythagorean fuzzy analytic hierarchy process." International Conference on Intelligent and Fuzzy Systems. Springer, Cham, 2019. https://doi.org/10.1007/978-3-030-23756-1_108
• 15. F. Kutlu Gündoğdu, and C. Kahraman, "A novel VIKOR method using spherical fuzzy sets and its application to warehouse site selection", Journal of Intelligent & Fuzzy Systems, vol. 37, no.1, , 2019, pp. https://doi.org/1197-1211.10.3233/JIFS-182651
• 16. S. Y. Roh, Y. R. Shin, and Y. J. Seo, “The Pre-positioned warehouse location selection for international humanitarian relief logistics”, The Asian Journal of Shipping and Logistics, vol.34, no.4, pp.297-307, 2018.
• 17. R. K. Singh, N. Chaudhary, and N. Saxena, “ Selection of warehouse location for a global supply chain: A case study”, IIMB Management Review, vol. 30, no.4, pp. 343-356, 2018.
• 18. N. Foroozesh, R. Tavakkoli-Moghaddam, and S. M. Mousavi, “A novel group decision model based on mean–variance–skewness concepts and interval-valued fuzzy sets for a selection problem of the sustainable warehouse location under uncertainty”, Neural Computing and Applications, vol.30, no.11, 2018, pp.3277-3293. https://doi.org/10.1007/s00521-017-2885-z
• 19. Ş. Emeç, and G. Akkaya, "Stochastic AHP and fuzzy VIKOR approach for warehouse location selection problem", Journal of Enterprise Information Management, vol. 31 no. 6, 2018, pp. 950-962. https://doi.org/10.1108/JEIM-12-2016-0195
• 20. B. Dey, B. Bairagi, B. Sarkar, and S. K. Sanyal, “Group heterogeneity in multi member decision making model with an application to warehouse location selection in a supply chain”, Computers & Industrial Engineering, vol.105, 2017, pp.101-122. https://doi.org/10.1016/j.cie.2016.12.025
• 21. G. T. Temur, “A novel multi attribute decision making approach for location decision under high uncertainty”, Applied Soft Computing, vol. 40, 2016, pp.674-682. https://doi.org/10.1016/j.asoc.2015.12.027
• 22. B. Dey, B. Bairagi, B. Sarkar, and S. K. Sanyal, “Warehouse location selection by fuzzy multi-criteria decision making methodologies based on subjective and objective criteria”, International Journal of Management Science and Engineering Management, vol.11, no.4, 2016, pp. 262-278. https://doi.org/10.1080/17509653.2015.1086964
• 23. B. Malmir, A. Aghighi, M. N. Bisheh, A. Ala, B. A., Avilaq, and S. Dehghani, “Application of a new multi criteria decision making method for warehouse location problem”, International Journal of Value Chain Management, vol.7, no.3, 2015, pp. 255-270. https://doi.org/10.1504/IJVCM.2016.079211
• 24. C. Karmaker, and M. Saha, “Optimization of warehouse location through fuzzy multi-criteria decision making methods”, Decision Science Letters, vol.4, no.3, 2015, pp.315-334. https://doi.org/10.5267/j.dsl.2015.4.005
• 25. B. Malmir, R. Moein, and S.K. Chaharsooghi, “Selecting warehouse location by means of the balancing and ranking method with an interval approach.” 2015 International Conference on Industrial Engineering and Operations Management (IEOM), IEEE, 2015, pp. 1-7. https://doi.org/10.1109/IEOM.2015.7093911
• 26. F. Uysal, and Ö. Tosun, “Selection of sustainable warehouse location in supply chain using the grey approach”, International Journal of Information and Decision Sciences, vol.6, no.4, 2014, pp.338-353. https://doi.org/10.1504/IJIDS.2014.066633
• 27. I. U. Sarı, B. Öztayşi, and C. Kahraman, Fuzzy analytic hierarchy process using type-2 fuzzy sets: An application to warehouse location selection. In Multicriteria decision aid and artificial intelligence, John Wiley & Sons, Ltd., 2013, pp. 285-308. https://doi.org/10.1002/9781118522516.ch12
• 28. B. Dey, B. Bairagi, B. Sarkar, and S. K. Sanyal, “A hybrid fuzzy technique for the selection of warehouse location in a supply chain under a utopian environment”, International Journal of Management Science and Engineering Management, vol.8, no.4, pp. 250-261, 2013.
• 29. B. Dey, B. Bairagi, B. Sarkar, and S. K. Sanyal, “A MOORA based fuzzy multi-criteria decision making approach for supply chain strategy selection”, International Journal of Industrial Engineering Computations, vol.3, no.4, 2012, pp. 649-662. https://doi.org/10.1080/17509653.2013.825075
• 30. T. Özcan, N. Çelebi, and Ş. Esnaf, “Comparative analysis of multi-criteria decision making methodologies and implementation of a warehouse location selection problem”, Expert Systems with Applications, vol.38, no.8, 2011, pp.9773-9779. https://doi.org/10.1016/j.eswa.2011.02.022
• 31. T. Demirel, Ç. Demirel, and C. Kahraman, “Multi-criteria warehouse location selection using Choquet integral”, Expert Systems with Applications, vol. 37, no.5, 2010, pp. 3943-3952. https://doi.org/10.1016/j.eswa.2009.11.022
• 32. Q. Cao, X. Di, and X. Zhang, A simulated annealing methodology to estate logistic warehouse location selection and distribution of customers' requirement. In 2009 International Workshop on Intelligent Systems and Applications, IEEE, May 2009, pp. 1-4. https://doi.org/10.1109/IWISA.2009.5072676
• 33. Ö. Senvar, U. R. Tuzkaya, and C. Kahraman, Supply chain performance measurement: an integrated DEMATEL and Fuzzy-ANP approach. In Supply Chain Management Under Fuzziness, Springer, Berlin, Heidelberg, 2014, pp. 143-165. https://doi.org/10.1007/978-3-642-53939-8_7
• 34. R.R. Yager, Properties and applications of Pythagorean fuzzy sets. In: Imprecision and Uncertainty in Information Representation and Processing. Springer, 2016, pp.119–136. https://doi.org/10.1007/978-3-319-26302-1_9
• 35. L., Abdullah and P. Goh, “Decision making method based on Pythagorean fuzzy sets and its application to solid waste management”, Complex & Intelligent Systems, vol. 5, no.2, 2019, pp. 185-198. https://doi.org/10.1007/s40747-019-0100-9

Uwagi

1. Track 1: Artificial Intelligence

2. Technical Session: 15th International Symposium Advances in Artificial Intelligence and Applications

3. Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).