نشریه علمی فرآیند نو

نشریه علمی فرآیند نو

مجموعه های فازی شهودی در ارزیابی عملکرد زنجیره تامین با استفاده از مدل مرجع عملیاتی زنجیره تامین

نوع مقاله : ترویجی

نویسندگان
1 دانشجوی دکتری مهندسی صنایع، دانشکده فنی و مهندسی، دانشگاه علوم و تحقیقات، تهران
2 دانشیار مهندسی صنایع، دانشکده فنی و مهندسی، دانشگاه علوم و تحقیقات، تهران
3 استادیار مهندسی صنایع، دانشکده فنی و مهندسی، دانشگاه آیندگان، تنکابن
4 استادیار مهندسی صنایع، دانشکده فنی و مهندسی، دانشگاه علوم و تحقیقات، تهران
چکیده
ارزیابی زنجیره تامین، کارکردهای متنوعی در بهبود عملکرد، مدیریت مطلوب منابع، شناسایی راهبردهای رفع چالش ­ها و ضعف­ های موجود در زنجیره ­تامین فعلی و نهایتا توسعه پایدار دارد. هدف شناسایی معیارها و زیرمعیارهای ارزیابی زنجیره­تامین با استفاده از ابعاد مدل مرجع عملیاتی زنجیره ­تامین در این شرکت بوده است. در این پژوهش، مدل عملیاتی زنجیره ­تامین به عنوان مرجع در نظر گرفته شده و زیرمعیارها با ابعاد قابلیت اطمینان، پاسخگویی، کیفیت، هزینه و مدیریت دارایی استخراج گردیده­اند. با استفاده از روش دیمتل، روابط علی و معلولی 24 زیرمعیار در محیط فازی شهودی تعریف شده و با روش فرآیند تحلیل شبکه با سه نوع داده قطعی و فازی و فازی شهودی وزن‌دهی شده اند. وزن­­دهی با سه روش، مقایسه شده که داده ­های فازی شهودی نتایج به مراتب با دقت بهتری را بدست آوردند و در نهایت واحدهای تصمیم گیری رتبه ­­بندی، که واحد تصمیم­ گیری یک بهترین رتبه و واحد هشتم بدترین رتبه را کسب کردند.
کلیدواژه‌ها

موضوعات


عنوان مقاله English

Intuitionistic fuzzy sets on Performance Evaluation of the supply chain using Supply chain operations reference (SCOR)

نویسندگان English

Ebrahim Golzar 1
seyyed esmaeil najafi 2
seyyed ahmad edalatpanah 3
amir azizi 4
1 PhD studnt of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran
2 Associate Professor of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran
3 Assistant Professor of Industrial Engineering, Ayandegan Institue of Higher Education, Tonokabon
4 Assistant Professor of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran
چکیده English

Evaluation of the supply chain encompasses various functions aimed at performance improvement, efficient resource management, identification of strategies to address current challenges and weaknesses in the existing supply chain, and ultimately, sustainable development of the company. Aimed to identify criteria and sub-criteria for evaluating the supply chain using dimensions of the operational supply chain model within this company. The operational supply chain model was adopted as a reference, and sub-criteria were extracted based on the dimensions of reliability, responsiveness, quality, cost, and asset management. Using the DEMATEL method, causal relationships among 24 sub-criteria were defined in a fuzzy Intuitionistic environment, and then weighted using the Analytic Network Process (ANP) with three types of data: crisp, fuzzy, and fuzzy cognitive. Weighting with all three methods was compared, showing that fuzzy Intuitionistic data yielded significantly more accurate results. Finally, decision-making units were ranked, with Decision Unit 1 achieving the highest rank and Decision Unit Eight the lowest.

کلیدواژه‌ها English

Supply Chain
SCOR
Intuitionistic Fuzzy
ANP
DEMATEL
[1] P. Akkawuttiwanich and P. Yenradee, "Fuzzy QFD approach for managing SCOR performance indicators," Computers & Industrial Engineering, vol. 122, pp. 189-201, 2018.
[2] B. M. Beamon, "Measuring supply chain performance," International journal of operations & production management, vol. 19, no. 3, pp. 275-292, 1999.
[3] G. Wang, S. H. Huang, and J. P. Dismukes, "Product-driven supply chain selection using integrated multi-criteria decision-making methodology," International journal of production economics, vol. 91, no. 1, pp. 1-15, 2004.
[4] M. Schulze, S. Seuring, and C. Ewering, "Applying activity-based costing in a supply chain environment," International Journal of Production Economics, vol. 135, no. 2, pp. 716-725, 2012.
[5] W.-H. Tsai and S.-J. Hung, "A fuzzy goal programming approach for green supply chain optimisation under activity-based costing and performance evaluation with a value-chain structure," International Journal of Production Research, vol. 47, no. 18, pp. 4991-5017, 2009.
[6] G. M. D. Ganga and L. C. R. Carpinetti, "A fuzzy logic approach to supply chain performance management," International Journal of Production Economics, vol. 134, no. 1, pp. 177-187, 2011. [7] S. H. Elgazzar, N. S. Tipi, N. J. Hubbard, and D. Z. Leach, "Linking supply chain processes’ performance to a company’s financial strategic objectives," European Journal of Operational Research, vol. 223, no. 1, pp. 276-289, 2012.
[8] V. Ravi, R. Shankar, and M. K. Tiwari, "Analyzing alternatives in reverse logistics for end-of-life computers: ANP and balanced scorecard approach," Computers & industrial engineering, vol. 48, no. 2, pp. 327-356, 2005.
[9] L. A. Zadeh, "Fuzzy sets," Information and control, vol. 8, no. 3, pp. 338-353, 1965.
[10] O. Kulak and C. Kahraman, "Fuzzy multi-attribute selection among transportation companies using axiomatic design and analytic hierarchy process," Information Sciences, vol. 170, no. 2-4, pp. 191-210, 2005.
[11] B. Kocaoğlu, B. Gülsün, and M. Tanyaş, "A SCOR based approach for measuring a benchmarkable supply chain performance," Journal of Intelligent Manufacturing, vol. 24, pp. 113-132, 2013.
[12] S. C. Council, "Supply chain operations reference model," Overview of SCOR version, vol. 5, no. 0, 2008.
[13] F. Herrera, E. Herrera-Viedma, and L. Martı́nez, "A fusion approach for managing multi-granularity linguistic term sets in decision making," Fuzzy sets and systems, vol. 114, no. 1, pp. 43-58, 2000.
[14] P. Bolstorff and R. Rosenbaum, "Supply chain excellence: A handbook for dramatic improvement using the SCOR model," Journal of Supply Chain Management, vol. 39, no. 4, p. 38, 2003.
[15] J. H. Malin and E. Reichardt, "Strengthen the six sigma portfolio," Quality, vol. 44, no. 6, p. 40, 2005.
[16] M. Alomar and Z. J. Pasek, "Linking supply chain strategy and processes to performance improvement," Procedia CIRP, vol. 17, pp. 628-634, 2014.
[17] R. Bhagwat and M. K. Sharma, "An application of the integrated AHP-PGP model for performance measurement of supply chain management," Production Planning & Control, vol. 20, no. 8, pp. 678-690, 2009.
[18] J. Gou, G. Shen, and R. Chai, "Model of service-oriented catering supply chain performance evaluation," Journal of Industrial Engineering and Management (JIEM), vol. 6, no. 1, pp. 215-226, 2013.
[19] F. T. Chan and H. J. Qi, "An innovative performance measurement method for supply chain management," Supply chain management: An international Journal, vol. 8, no. 3, pp. 209-223, 2003. [20] R. Bhagwat and M. K. Sharma, "Performance measurement of supply chain management using the analytical hierarchy process," Production planning and control, vol. 18, no. 8, pp. 666-680, 2007.
[21] A. Najmi and A. Makui, "Providing hierarchical approach for measuring supply chain performance using AHP and DEMATEL methodologies," International Journal of Industrial Engineering Computations, vol. 1, no. 2, pp. 199-212, 2010.
[22] A. Moharamkhani, A. Bozorgi-Amiri, and H. Mina, "Supply chain performance measurement using SCOR model based on interval-valued fuzzy TOPSIS," International Journal of Logistics Systems and Management, vol. 27, no. 1, pp. 115-132, 2017.
[23] M. A. El-Baz, "Fuzzy performance measurement of a supply chain in manufacturing companies," Expert Systems with Applications, vol. 38, no. 6, pp. 6681-6688, 2011.
[24] W. Zhihong, W. Yan, and W. He, "Performance evaluation indicator system and model construction of the green supply chain," in 2013 Third International Conference on Intelligent System Design and Engineering Applications, 2013: IEEE, pp. 1042-1044.
[25] R.-J. Lin, "Using fuzzy DEMATEL to evaluate the green supply chain management practices," Journal of cleaner production, vol. 40, pp. 32-39, 2013.
[26] P. Bolstorff and R. G. Rosenbaum, Supply chain excellence: a handbook for dramatic improvement using the SCOR model. AMACOM.American Management Association, 2007.
[27] K. T. Atanassov and K. T. Atanassov, Intuitionistic fuzzy sets. Springer, 1999.
[28] H. M. Nehi and H. R. Maleki, "Intuitionistic fuzzy numbers and it's applications in fuzzy optimization problem," in Proceedings of the 9th WSEAS International Conference on Systems, 2005, pp. 1-5.
[29] J. Ye, "Expected value method for intuitionistic trapezoidal fuzzy multicriteria decision-making problems," Expert Systems with Applications, vol. 38, no. 9, pp. 11730-11734, 2011.
[30] S. Datta, C. Samantra, S. S. Mahapatra, G. Mondal, P. S. Chakraborty, and G. Majumdar, "Selection of internet assessment vendor using TOPSIS method in fuzzy environment," International Journal of Business Performance and Supply Chain Modelling, vol. 5, no. 1, pp. 1-27, 2013.
[31] P. Phochanikorn and C. Tan, "A new extension to a multi-criteria decision-making model for sustainable supplier selection under an intuitionistic fuzzy environment," Sustainability, vol. 11, no. 19, p. 5413, 2019.
[32] T. L. Saaty, Theory and applications of the analytic network process: decision making with benefits, opportunities, costs, and risks. RWS publications, 2005.