تحلیل تطبیقی رویکردهای تصمیم گیری چند معیاره خاکستری در اولویت بندی تأمین‌کنندگان (فولاد مبارکه اصفهان)
محورهای موضوعی : مدیریت صنعتیAhmad Reza Ghasemi 1 , Hashem Mozzez 2 , Fatemeh Abedi Jebeli 3
1 - Assistant Professor Industrial Management, Faculty of Management & Accounting, Farabi Compus University of Tehran
2 - Assistant Professor Industrial Management, Faculty of Management & Accounting, Farabi Compus University of Tehran
3 - Master of Industrial Management, Faculty of Management & Accounting, Farabi Compus University of Tehran
کلید واژه: Supplier selection, انتخاب تأمین‌کننده, تصمیم‌گیری چند معیاره خاکستری, عدد خاکستری, کوپراس خاکستری, MCDM-G, Grey Number, COPRAS-G,
چکیده مقاله :
زنجیره تأمین اخیراً نظر بسیاری از محققین را به خود جلب کرده است. هدف این مقاله، شناسایی تأمین‌کنندگانی است که بیشترین توان بالقوه را در برآورده ساختن نیازهای شرکت با صرف هزینه معقولانه، داشته باشند و همچنین کاهش ریسک و حداکثر کردن ارزش کلی برای خریداران است. ازآنجایی‌که تأمین‌کنندگان ازلحاظ نقاط قوت و ضعف و شرایط عمومی محصولاتشان متفاوت هستند، نیازمند ارزیابی دقیق به‌وسیله خریداران می‌باشند. جهت انجام این فعالیت‌ها در شرکت‌ها، مشکلات فراوانی وجود دارد که یکی از آن مشکلات مربوط به تعیین معیارهای مناسب جهت ارزیابی تأمین‌کننده است. این موضوع به این دلیل است که غالباً نیازها در قالب مفاهیم کیفی اظهار می‌شوند درحالی‌که باید به‌صورت کمی مورد ارزیابی قرار گیرند. علاوه بر این، ازنظر تصمیم‌گیرنده، معیارها نسبت به یکدیگر از اهمیت و اولویت متفاوتی برخوردار می‌باشند و این موضوع یکی از دلایل اصلی است که نگارندگان را بر آن داشت که به دنبال ارائه الگویی باشند تا به‌وسیله آن بتوان انتخاب تأمین‌کننده را بر اساس معیارهای مناسب و با تأکید بر میزان اهمیت هر یک از آن‌ها در فرآیند تصمیم‌گیری انجام داد. بدین منظور ابتدا بامطالعه ادبیات موضوع، معیارهای مؤثر در انتخاب تأمین‌کنندگان شناسایی شدند، سپس با استفاده از پرسشنامه‌ای که توسط گروهی از کارشناسان تکمیل شد به غربالگری شاخص‌ها پرداخته شد. داده‌های کمی و کیفی شاخص‌های انتخاب‌شده جمع‌آوری شدند و توسط روش AHP درجه اهمیت معیارهای مؤثر در انتخاب تأمین‌کنندگان مشخص شد و درنهایت تأمین‌کنندگان شرکت با روش کوپراس خاکستری رتبه‌بندی شدند. مهم ترین معیار جهت ارزیابی تأمین‌کنندگان دارایی و زیرساخت (275/0) و تأمین‌کننده بهران به‌عنوان بهترین تأمین‌کننده شناسایی شد.
The supply chain has recently attracted the attention of many researchers. The purpose of this paper is to identify Suppliers that have the highest potential capacity to meet the needs companies, with reasonable cost and also reduce the risk and maximize the total value of purchaser. Since suppliers are different in terms of products strengths and weaknesses and general conditions, requires a careful evaluation by the purchaser. In order to do this activity in the Companies, there are many problems; one of those problems is to determine the appropriate criteria for assessing supplier. This is because often need to be expressed in the form of qualitative concepts, while they must be evaluated quantitatively. In addition, in terms of decision makers, importance and priorities of each criterion are different, and this is one of the main reasons that authors are seeking to present a model to select suppliers based on appropriate criteria with emphasis on the importance degree of them in the decision-making process. So at first with reviewing the literature, criteria influencing the choice of suppliers were identified, then using a questionnaire that was completed by a Team of experts to screening criteria was discussed. The qualitative and quantitative data were collected and the importance of effective criteria in supplier selection determined by AHP method and finally suppliers of this company ranked using Grey COPRAS method. The most important criteria for evaluation supplier were assets and infrastructure (0.275) and Behran supplier was identified as the best supplier.
1. Azar, A., & Faraji, H. (2008). Fuzzy Management Science. Publications kind Publishing. Tehran.
2. Asgharizadeh, E. & Ghasemi, AR. (2011). The path supply chain performance excellence, the new indicator in assessing competitiveness and Corporate Excellence (Case study: supply chain department stores citizenship). Business Research Quarterly, 13)2(, 65-72.
3. Burgess, K., Singh, P. J., & Koroglu, R. (2006). Supply chain management: a structured literature review and implications for future research. International Journal of Operations & Production Management, 26(7), 703-729.
4. Chen, C. T., Lin, C. T., & Huang, S. F. (2006). A fuzzy approach for supplier evaluation and selection in supply chain management. International journal of production economics, 102(2), 289-301.
5. Darabi, M. & Saeedi, S. (2008). Design an integrated model for evaluating the performance of suppliers and allocating orders using multi-objective DEA models and planning. Journal Automotive Eng and related industries (first year), No. 4.
6. De Boer, L., Labro, E., & Morlacchi, P. (2001). A review of methods supporting supplier selection. European journal of purchasing & supply management, 7(2), 75-89.
7. Ju-Long, D. (1982). Control problems of grey systems. Systems & Control Letters, 1(5), 288-294.
8. Dou, Y., Zhu, Q., & Sarkis, J. (2014). Evaluating green supplier development programs with a grey-analytical network process-based methodology. European Journal of Operational Research, 233(2), 420-431.
9. Faraji, S. H., Motieei, L. S., Yadollahi, F. J., & Karimzadeh, H. (2012). Ranking the development of tourism and its backgrounds in rural areas, using gray topsis (Case study: rural areas of varzaghan township). Journal of Rural Research, 3(1), 1-6.
10. Ghafarian, V. (2000). Man, computer and decision-making, an analytical review of decision support systems. Journal of prudence, 108.
11. Ghazanfari, M. Riazi, A. Kazemi, M. (2001). Supply chain management and the importance of relationships. Journal of prudence, 117.
12. Ghodsi poor, S. H. (2006). Multi Objective Programming. (Second Edition). Publications Amirkabir University of Technology, Tehran
13. Ha, S. H., & Krishnan, R. (2008). A hybrid approach to supplier selection for the maintenance of a competitive supply chain. Expert Systems with Applications, 34(2), 1303-1311.
14. Hoshmandi Maher, M. (2006). Designing mathematical model using Multiple Criteria Decision Making, Case Studies department stores citizenship: Beyhaghi terminal. (Master's thesis). Faculty of Management and Accounting, Allameh Tabatabaei University.
15. Mohaghar, A. Noori, M. Mirkazemi, M. Sarabi, N. (2011). Selection of suppliers of engineering and construction companies. Journal Excavations of Business Management, 3(6), 22-50.
16. Russell, D. M. Anne, M. Hoag (2007). People and information technology in the supply chain: Social and organizational influences on adoption. International Journal of Physical Distribution & Logistics Management, 34(2),102-122.
17. Saaty, T. (1989). Group decision making and the AHP, in: B.L. Gdden, E.A. Wasil, P.T. Harket, The Analytic Hierarchy Process. Application and Studies, Springer, New York, 12(2), 59-67.
18. Maity, S. R., Chatterjee, P., & Chakraborty, S. (2012). Cutting tool material selection using grey complex proportional assessment method. Materials & Design, 36, 372-378.
19. Datta, S., Sahu, N., & Mahapatra, S. (2013). Robot selection based on grey-MULTIMOORA approach. Grey Systems: Theory and Application, 3(2), 201-232.
20. Shafiee, S. Ahadi, H. (2010). A combination of multiple criteria decision making model for supplier selection metro equipment. The First National Conference on Localization of Iranian Rail Industries,Tehran.
21. Ting, S. C., & Cho, D. I. (2008). An integrated approach for supplier selection and purchasing decisions. Supply Chain Management: An International Journal, 13(2), 116-127.
22. Wilson, D. Mit. Jr. (2000). Managing a global supply chain whit durable arm's -length supplier relationship. International Journal of Productivity and Performance Management, 30(1), 7-25.
23. Lin, Y. H., Lee, P. C., & Ting, H. I. (2008). Dynamic multi-attribute decision making model with grey number evaluations. Expert Systems with Applications, 35(4), 1638-1644.
24. Zavadskas, E. K., Turskis, Z., & Tamošaitiene, J. (2010). Risk assessment of construction projects. Journal of civil engineering and management, 16(1), 33-46.
25. Zolfani, S. H., Sedaghat, M., & Zavadskas, E. K. (2012). Performance evaluating of rural ICT centers (telecenters), applying fuzzy AHP, SAW-G and TOPSIS Grey, a case study in Iran. Technological and Economic Development of Economy, 18(2), 364-387.
_||_1. Azar, A., & Faraji, H. (2008). Fuzzy Management Science. Publications kind Publishing. Tehran.
2. Asgharizadeh, E. & Ghasemi, AR. (2011). The path supply chain performance excellence, the new indicator in assessing competitiveness and Corporate Excellence (Case study: supply chain department stores citizenship). Business Research Quarterly, 13)2(, 65-72.
3. Burgess, K., Singh, P. J., & Koroglu, R. (2006). Supply chain management: a structured literature review and implications for future research. International Journal of Operations & Production Management, 26(7), 703-729.
4. Chen, C. T., Lin, C. T., & Huang, S. F. (2006). A fuzzy approach for supplier evaluation and selection in supply chain management. International journal of production economics, 102(2), 289-301.
5. Darabi, M. & Saeedi, S. (2008). Design an integrated model for evaluating the performance of suppliers and allocating orders using multi-objective DEA models and planning. Journal Automotive Eng and related industries (first year), No. 4.
6. De Boer, L., Labro, E., & Morlacchi, P. (2001). A review of methods supporting supplier selection. European journal of purchasing & supply management, 7(2), 75-89.
7. Ju-Long, D. (1982). Control problems of grey systems. Systems & Control Letters, 1(5), 288-294.
8. Dou, Y., Zhu, Q., & Sarkis, J. (2014). Evaluating green supplier development programs with a grey-analytical network process-based methodology. European Journal of Operational Research, 233(2), 420-431.
9. Faraji, S. H., Motieei, L. S., Yadollahi, F. J., & Karimzadeh, H. (2012). Ranking the development of tourism and its backgrounds in rural areas, using gray topsis (Case study: rural areas of varzaghan township). Journal of Rural Research, 3(1), 1-6.
10. Ghafarian, V. (2000). Man, computer and decision-making, an analytical review of decision support systems. Journal of prudence, 108.
11. Ghazanfari, M. Riazi, A. Kazemi, M. (2001). Supply chain management and the importance of relationships. Journal of prudence, 117.
12. Ghodsi poor, S. H. (2006). Multi Objective Programming. (Second Edition). Publications Amirkabir University of Technology, Tehran
13. Ha, S. H., & Krishnan, R. (2008). A hybrid approach to supplier selection for the maintenance of a competitive supply chain. Expert Systems with Applications, 34(2), 1303-1311.
14. Hoshmandi Maher, M. (2006). Designing mathematical model using Multiple Criteria Decision Making, Case Studies department stores citizenship: Beyhaghi terminal. (Master's thesis). Faculty of Management and Accounting, Allameh Tabatabaei University.
15. Mohaghar, A. Noori, M. Mirkazemi, M. Sarabi, N. (2011). Selection of suppliers of engineering and construction companies. Journal Excavations of Business Management, 3(6), 22-50.
16. Russell, D. M. Anne, M. Hoag (2007). People and information technology in the supply chain: Social and organizational influences on adoption. International Journal of Physical Distribution & Logistics Management, 34(2),102-122.
17. Saaty, T. (1989). Group decision making and the AHP, in: B.L. Gdden, E.A. Wasil, P.T. Harket, The Analytic Hierarchy Process. Application and Studies, Springer, New York, 12(2), 59-67.
18. Maity, S. R., Chatterjee, P., & Chakraborty, S. (2012). Cutting tool material selection using grey complex proportional assessment method. Materials & Design, 36, 372-378.
19. Datta, S., Sahu, N., & Mahapatra, S. (2013). Robot selection based on grey-MULTIMOORA approach. Grey Systems: Theory and Application, 3(2), 201-232.
20. Shafiee, S. Ahadi, H. (2010). A combination of multiple criteria decision making model for supplier selection metro equipment. The First National Conference on Localization of Iranian Rail Industries,Tehran.
21. Ting, S. C., & Cho, D. I. (2008). An integrated approach for supplier selection and purchasing decisions. Supply Chain Management: An International Journal, 13(2), 116-127.
22. Wilson, D. Mit. Jr. (2000). Managing a global supply chain whit durable arm's -length supplier relationship. International Journal of Productivity and Performance Management, 30(1), 7-25.
23. Lin, Y. H., Lee, P. C., & Ting, H. I. (2008). Dynamic multi-attribute decision making model with grey number evaluations. Expert Systems with Applications, 35(4), 1638-1644.
24. Zavadskas, E. K., Turskis, Z., & Tamošaitiene, J. (2010). Risk assessment of construction projects. Journal of civil engineering and management, 16(1), 33-46.
25. Zolfani, S. H., Sedaghat, M., & Zavadskas, E. K. (2012). Performance evaluating of rural ICT centers (telecenters), applying fuzzy AHP, SAW-G and TOPSIS Grey, a case study in Iran. Technological and Economic Development of Economy, 18(2), 364-387.