بهینه‌سازی زنجیره تامین حلقه بسته با رویکرد پایداری با استفاده از تصمیم گیری چندهدفه و روش DANP در صنعت غذا: مطالعه موردی در صنعت لبنی
محورهای موضوعی : مدیریت صنعتی
azam khabooshani
1
(Department of Management, Azad university of Isfahan, Isfahan, Iran)
ommolbanin yousefi
2
(Department of Industrial Engineering, Malek Ashtar University of Technology, Isfahan, Iran)
mahdi fadaee
3
(Assistant professor, Department of Economic, Payamenoor University, Iran)
Iraj Soltani
4
(Department of Management, Azad Universty of Isfahan, Isfahan, Iran)
کلید واژه: پایدار, زنجیره تأمین حلقه بسته, دنپ, تصمیم‌گیری چندهدفه, L-P متریک,
چکیده مقاله :
در این مقاله یک مدل برنامه‌ریزی عدد صحیح مختلط چندهدفه، چند محصولی جهت برنامه‌ریزی تولید،توزیع،حمل‌ونقل با در نظر گرفتن شاخص‌های پایداری در شبکه زنجیره تأمین حلقه بسته صنعت غذا ارائه شده است. ابتدا پس از مرور ادبیات موضوع و با استفاده از نظرات خبرگان دانشگاه و صنعت غذا مهم‌ترین شاخص‌های پایداری با ابعاد سه‌گانه اقتصادی،زیست‌محیطی و اجتماعی در این صنعت،استخراج و ساختار روابط شبکه و میزان تأثیرگذاری و تأثیرپذیری هریک از شاخص‌ها از طریق تکنیک دیمتل تعیین شده‌اند سپس این تکنیک با روش فرآیند تحلیل شبکه‌ای به‌منظور تعیین اوزان هر بعد و شاخص‌های آن ترکیب گردیده و درنهایت شاخص‌های دارای اولویت بالاتر انتخاب شده‌اند.در ادامه یک مدل ریاضی عدد صحیح مختلط جهت برنامه‌ریزی تولید،توزیع،حمل‌ونقل زنجیره تأمین پایدار حلقه بسته با ابعاد سه‌گانه فوق‌الذکر ارائه شده است که در آن شاخص‌های حاصل از تکنیک دنپ،هزینه کل از بعد اقتصادی با وزن 1301/0مصرف آب و مصرف انرژی از بعد زیست‌محیطی با اوزان0578/0، 0580/0و فرصت‌های شغلی از بعد اجتماعی با وزن0911/0به‌عنوان توابع هدف مدل‌سازی شده سپس با روش L-P متریک و با استفاده از نرم‌افزار گمز حل‌شده‌اند و مجموعه جواب‌های بهینه پارتویی به دست آمده است در پایان مطالعه موردی درزمینه صنایع لبنی به کمک داده‌های واقعی صورت گرفته است. اجرای مدل منجر به یافتن 8 دسته جواب بهینه پارتویی شده به‌طوری‌که کمترین میزان هزینه در بین جواب‌ها حدود 68 میلیون ریال در ماه، کمترین میزان مصرف آب حدود 660 مترمکعب در ماه و بیشترین میزان فرصت‌های اشتغال حدود 39 هزار نفر ساعت در ماه می‌باشد.
This paper presents a multi-purpose, multi-product mixed integer planning model considering the sustainability criteria to plan production, distribution, transportation in the food industry’s closed-loop supply chain. After reviewing the literature on the subject and using the opinions of university and food industry experts determining the most important sustainability indices with the three economic, environmental and social dimensions in the food industry, the relationship structure and effectiveness and impressionability levels of each indices were determined by DEMATEL technique and The technique is combined with a analysis network process to determine the weights of dimensions and their indices. In the second step, a mixed integer mathematical model was presented for planning the production, distribution, transportation of sustainable closed-loop supply chain dimensions with the above three dimensions, in which indicators from the DANP technique. Total cost of economic dimension of weighting 0/0101, for environmental dimension water consumption and energy consumption with weightings of 0/0578, 0/0580 and job opportunities of social dimension for weighting of 0/0911 modeled as goal functions. Then with the L-P metric method was solved by using GAMS and some optimal Pareto solutions were obtained. At the end, a case study was performed on the dairy industry with the help of Real data. Based on the solutions obtained, the lowest cost was found to be about 68 million rial per month, the lowest consumption rate of water was found to be about 660 m3 per month and the highest employment opportunities was found to be 39,000 man hours per month.
1- Allaoui, H., Guo, Y., Choudhary, A., & Bloemhof, J. (2018). Sustainable agro-food supply chain design using two-stage hybrid multi-objective decision-making approach. Computers & Operations Research, 89, 369-384.
2- Asgharpour, M. J. (2009). Multi-criteria decision making. Tehran: Tehran University Publications. (In Persian)
3- Azadeh, A., Raoofi, Z., & Zarrin, M. (2015). A multi-objective fuzzy linear programming model for optimization of natural gas supply chain through a greenhouse gas reduction approach. Journal of Natural Gas Science and Engineering, 26, 702-710.
4- Bavarsad, B., nili ahmadabadi, m., & beiranvand, t. (2018). Developing a Sustainable Supply Chain Management Model in Marine Industries Case study: Marine Industries Organization. Journal of Science Education,, 5(1), 29-40. (In Persian)
5- Chaabane, A., Ramudhin, A., & Paquet, M. J. I. j. o. p. e. (2012). Design of sustainable supply chains under the emission trading scheme.International Journal of Production Economics, 135(1), 37-49.
6- Christopher, M., & Holweg, M. (2011). " Supply Chain 2.0": managing supply chains in the era of turbulence. International journal of physical distribution logistics management, 41(1), 63-82.
7- Dehaghani, M. & Shahverdiani, SH and Musa Pour, H. (2018). Investigating the relationship between sustainable supply chain management with environmental performance and financial performance. Journal of Business Research: 85,171-194 (In Persia)
8- Elkington, J., & Rowlands, I. H. J. A. J. (1999). Cannibals with forks: the triple bottom line of 21st century business. 25(4), 42.
9- Fatemi Amin, S., & Mortazaei, A. (2014). The Food Products Supply Chain Strategic Plan. In: Tehran: Iranian Academic Center for Education, Culture & Research, Beheshti . (Persian)
10- Ghasemi, A., Rayatpisheh, M. A., Haddadi, A., & Rayat pisheh, S. (2017). Identification and Prioritization of Indicators Involved in Agricultural Supply Chain Sustainability. Environmental Science and Technology, 19(4), 369-382. doi:10.22034/JEST.2017.10738. (Persian)
11- Jafarnejad, A., & Bana Molaei, A. A. (2014). Investigation of the Impact of Sustainable Supply Chain ManagementDimensions on Supply Chain Operational Performance Using Structural Equation Modeling and Conventional Correlation Analysis. (Masters), University of Tehran (67487). (Persian)
1 12-Mahmoodi, A. (2014). Sustainable Supply Chain, Mehraban Book Publishing. (In Persian)
13- Nasab, N. M., & Amin-Naseri, M. J. E. (2016). Designing an integrated model for a multi-period, multi-echelon and multi-product petroleum supply chain. 114, 708-733.
14- Pishvaee, M. S., Razmi, J., & Torabi, S. A. (2014). An accelerated Benders decomposition algorithm for sustainable supply chain network design under uncertainty: A case study of medical needle and syringe supply chain. Logistics and Transportation Revie, 67, 14-38.
15- Pishvaee, M. S., & Razmi, J. J. A. M. M. (2012). Environmental supply chain network design using multi-objective fuzzy mathematical programming.Applied Mathematical Modelling, 36(8), 3433-3446.
16- Razmi, j., zahedi-anaraki, a. & zakerinia, m. 2013. A bi-objective stochastic optimization model for reliable warehouse network redesign. Mathematical and Computer Modelling, 58, 1804-1813.
17- Resat, H. G., Unsal, B. J. S. P., & Consumption. (2019). A novel multi-objective optimization approach for sustainable supply chain: A case study in packaging industry. Sustainable production & consumption, 20, 29-39.
18- Rohmer, S., Gerdessen, J. C., & Claassen, G. J. E. J. o. O. R. (2019). Sustainable supply chain design in the food system with dietary considerations: A multi-objective analysis. 273(3), 1149-1164.
19- Sahebjamnia, N., Fathollahi-Fard, A. M., & Hajiaghaei-Keshteli, M. J. J. o. c. p. (2018). Sustainable tire closed-loop supply chain network design: Hybrid metaheuristic algorithms for large-scale networks. Journal of cleaner production, 196, 273-296.
20- Sgarbossa, F., & Russo, I. (2017). A proactive model in sustainable food supply chain: Insight from a case study. Int. Journal production Economics. 183, 596-606.
21- Sunil Luthra , Sachin komar mangla.(2018 ). Adoption of sustainable supply chain management practices in an emerging economy’s context .Resources , conservation & Recycling 138.194-206
22- Taleizadeh, A. A., Haghighi, F., & Niaki, S. T. A. J. J. o. c. p. (2019 .(Modeling and solving a sustainable closed loop supply chain problem with pricing decisions and discounts on returned products. Journal of cleaner production, 207, 163-181.
23- Tseng, S.-C., & Hung, S.-W. J. J. o. e. m. (2014). A strategic decision-making model considering the social costs of carbon dioxide emissions for sustainable supply chain management Journal of environmentalmanagement, 315-332,133.
24- Yakovleva, N., Sarkis, J., & Sloan, T. (2010). Sustainability indicators for the food supply chain. In Environmental Assessment and Management in the Food Industry (pp. 297-329): Elsevier.
25- Zareian Jahromi, H., Fallahnejad, M., Sadeghieh, A., & Ahmadi Yazdi, A. (2014). Multi-objective optimization model based on sustainable closed loop supply chain design. Journal of Industrial Engineering Research, 2(3), 93-111. (Persian)
26- Zegordi, S. H., Eskandarpour, M., & Nikbakhsh, E. (2011). A novel bi-objective multi-product post-sales reverse logistics network design model. Paper presented at the Proceedings of the world congress on engineering.
_||_1- Allaoui, H., Guo, Y., Choudhary, A., & Bloemhof, J. (2018). Sustainable agro-food supply chain design using two-stage hybrid multi-objective decision-making approach. Computers & Operations Research, 89, 369-384.
2- Asgharpour, M. J. (2009). Multi-criteria decision making. Tehran: Tehran University Publications. (In Persian)
3- Azadeh, A., Raoofi, Z., & Zarrin, M. (2015). A multi-objective fuzzy linear programming model for optimization of natural gas supply chain through a greenhouse gas reduction approach. Journal of Natural Gas Science and Engineering, 26, 702-710.
4- Bavarsad, B., nili ahmadabadi, m., & beiranvand, t. (2018). Developing a Sustainable Supply Chain Management Model in Marine Industries Case study: Marine Industries Organization. Journal of Science Education,, 5(1), 29-40. (In Persian)
5- Chaabane, A., Ramudhin, A., & Paquet, M. J. I. j. o. p. e. (2012). Design of sustainable supply chains under the emission trading scheme.International Journal of Production Economics, 135(1), 37-49.
6- Christopher, M., & Holweg, M. (2011). " Supply Chain 2.0": managing supply chains in the era of turbulence. International journal of physical distribution logistics management, 41(1), 63-82.
7- Dehaghani, M. & Shahverdiani, SH and Musa Pour, H. (2018). Investigating the relationship between sustainable supply chain management with environmental performance and financial performance. Journal of Business Research: 85,171-194 (In Persia)
8- Elkington, J., & Rowlands, I. H. J. A. J. (1999). Cannibals with forks: the triple bottom line of 21st century business. 25(4), 42.
9- Fatemi Amin, S., & Mortazaei, A. (2014). The Food Products Supply Chain Strategic Plan. In: Tehran: Iranian Academic Center for Education, Culture & Research, Beheshti . (Persian)
10- Ghasemi, A., Rayatpisheh, M. A., Haddadi, A., & Rayat pisheh, S. (2017). Identification and Prioritization of Indicators Involved in Agricultural Supply Chain Sustainability. Environmental Science and Technology, 19(4), 369-382. doi:10.22034/JEST.2017.10738. (Persian)
11- Jafarnejad, A., & Bana Molaei, A. A. (2014). Investigation of the Impact of Sustainable Supply Chain ManagementDimensions on Supply Chain Operational Performance Using Structural Equation Modeling and Conventional Correlation Analysis. (Masters), University of Tehran (67487). (Persian)
1 12-Mahmoodi, A. (2014). Sustainable Supply Chain, Mehraban Book Publishing. (In Persian)
13- Nasab, N. M., & Amin-Naseri, M. J. E. (2016). Designing an integrated model for a multi-period, multi-echelon and multi-product petroleum supply chain. 114, 708-733.
14- Pishvaee, M. S., Razmi, J., & Torabi, S. A. (2014). An accelerated Benders decomposition algorithm for sustainable supply chain network design under uncertainty: A case study of medical needle and syringe supply chain. Logistics and Transportation Revie, 67, 14-38.
15- Pishvaee, M. S., & Razmi, J. J. A. M. M. (2012). Environmental supply chain network design using multi-objective fuzzy mathematical programming.Applied Mathematical Modelling, 36(8), 3433-3446.
16- Razmi, j., zahedi-anaraki, a. & zakerinia, m. 2013. A bi-objective stochastic optimization model for reliable warehouse network redesign. Mathematical and Computer Modelling, 58, 1804-1813.
17- Resat, H. G., Unsal, B. J. S. P., & Consumption. (2019). A novel multi-objective optimization approach for sustainable supply chain: A case study in packaging industry. Sustainable production & consumption, 20, 29-39.
18- Rohmer, S., Gerdessen, J. C., & Claassen, G. J. E. J. o. O. R. (2019). Sustainable supply chain design in the food system with dietary considerations: A multi-objective analysis. 273(3), 1149-1164.
19- Sahebjamnia, N., Fathollahi-Fard, A. M., & Hajiaghaei-Keshteli, M. J. J. o. c. p. (2018). Sustainable tire closed-loop supply chain network design: Hybrid metaheuristic algorithms for large-scale networks. Journal of cleaner production, 196, 273-296.
20- Sgarbossa, F., & Russo, I. (2017). A proactive model in sustainable food supply chain: Insight from a case study. Int. Journal production Economics. 183, 596-606.
21- Sunil Luthra , Sachin komar mangla.(2018 ). Adoption of sustainable supply chain management practices in an emerging economy’s context .Resources , conservation & Recycling 138.194-206
22- Taleizadeh, A. A., Haghighi, F., & Niaki, S. T. A. J. J. o. c. p. (2019 .(Modeling and solving a sustainable closed loop supply chain problem with pricing decisions and discounts on returned products. Journal of cleaner production, 207, 163-181.
23- Tseng, S.-C., & Hung, S.-W. J. J. o. e. m. (2014). A strategic decision-making model considering the social costs of carbon dioxide emissions for sustainable supply chain management Journal of environmentalmanagement, 315-332,133.
24- Yakovleva, N., Sarkis, J., & Sloan, T. (2010). Sustainability indicators for the food supply chain. In Environmental Assessment and Management in the Food Industry (pp. 297-329): Elsevier.
25- Zareian Jahromi, H., Fallahnejad, M., Sadeghieh, A., & Ahmadi Yazdi, A. (2014). Multi-objective optimization model based on sustainable closed loop supply chain design. Journal of Industrial Engineering Research, 2(3), 93-111. (Persian)
26- Zegordi, S. H., Eskandarpour, M., & Nikbakhsh, E. (2011). A novel bi-objective multi-product post-sales reverse logistics network design model. Paper presented at the Proceedings of the world congress on engineering.