نوآوری‌های صنعتی

نوآوری‌های صنعتی

طراحی شبکه زنجیره‌تأمین پایدار بر اساس شاخص‌های ایجاد ارزش (مطالعه موردی صنعت تایر خودرو)

نوع مقاله : مقاله پژوهشی

نویسندگان
گروه مهندسی صنایع، دانشکده فنی و مهندسی، دانشگاه علم و فرهنگ، تهران، ایران.
چکیده
طراحی زنجیره تأمین در دنیای امروز نیازمند ایجاد توازن میان اهداف متضاد اقتصادی و الزامات پایداری است. پژوهش حاضر با هدف ارائه یک مدل ریاضی برای طراحی زنجیره تأمین پایدار حلقه بسته انجام‌شده که به‌طور هم‌زمان سه بعد سودآوری، زیست‌محیطی و اجتماعی را پوشش می‌دهد. نوآوری این مقاله، در نظر گرفتن هم‌زمان شاخص توسعه انسانی (HDI) و شاخص ایجاد ارزش در یک زنجیره حلقه بسته در صنعت تایر در ایران است. در مقاله پایه‌ای که این مسأله از آن الگو گرفته شده است، زنجیره تأمین روبه‌جلو در نظر گرفته شده است. برای مدلسازی مسأله، یک مدل برنامه‌ریزی خطی عددصحیح مختلط دوهدفه توسعه داده شد که تابع هدف اول بیشینه‌سازی سودآوری و تابع هدف دوم کمینه‌سازی انتشار گاز دی‌اکسید کربن در تسهیلات و مسیرهای حمل‌ونقل را دنبال می‌کند. برای لحاظ کردن بعد اجتماعی پایداری، شاخص توسعه انسانی (HDI) به‌صورت محدودیت به مدل اضافه شده است. مدل پیشنهادی ابتدا با ابعاد کوچک و استفاده از روش‌های حل دقیق اعتبارسنجی شد. سپس با توجه به پیچیدگی مسأله، دو الگوریتم فراابتکاری چندهدفه برای حل آن در ابعاد واقعی توسعه یافته و کارایی آنها با جواب‌های دقیق مقایسه شد. نتایج حاکی از کارایی مطلوب الگوریتم‌های فراابتکاری در دستیابی به جواب‌های نزدیک به بهینه با زمان محاسباتی کوتاه است. تحلیل حساسیت‌های انجام‌شده نیز نشان می‌دهد که لحاظ کردن هم‌زمان ملاحظات پایداری، تأثیر معناداری بر امکان‌پذیری و پیکربندی نهایی شبکه زنجیره تأمین دارد. مدل ارائه‌شده می‌تواند به‌عنوان ابزاری تحلیلی در اختیار مدیران قرار گیرد تا روابط پیچیده میان سودآوری و پایداری را بهتر درک کرده و تصمیمات آگاهانه‌تری در طراحی شبکه زنجیره تأمین اتخاذ نمایند.
کلیدواژه‌ها

عنوان مقاله English

Sustainable Supply Chain Network Design Based on Value - Creation Indices (Case Study: Tire Industry)

نویسندگان English

Morteza Khakzar Bafruei
Majid Torabi
Mohadeseh Khosravi
Industrial Engineering Department, Engineering Faculty, University of Science and Culture, Tehran, Iran.
چکیده English

Supply chain design in today 's world requires a balance between conflicting economic goals and sustainability requirements. The aim of this study is to present a mathematical model for sustainable supply chain design which covers three dimensions of profitability, environmental and social. The innovation of this paper lies in the simultaneous consideration of the Human Development Index (HDI) and the value creation index within a closed-loop supply chain in the Iranian tire industry. In the baseline paper from which this problem was modeled, only the forward supply chain was taken into account. A bi-objective mixed integer linear programming (MILP) model was developed which follows the first objective function to maximize the profitability and the second objective function to minimize the co2 emissions in the transportation facilities and routes. The human development index was added to the model to account for the social dimension of sustainability. The proposed model was validated with small dimensions and using exact solution methods. Then, due to the complexity of the problem, two metaheuristic algorithms have been developed to solve it in real dimensions and their performance is compared with the exact solutions. The results indicate that metaheuristic algorithms have good performance in achieving the optimal solutions with short computational time. The sensitivity analysis also shows that considering sustainability considerations, it has a significant effect on the feasibility and final configuration of the supply chain network. The proposed model can be used as an analytical tool to managers to better understand complex relationships between profitability and sustainability and make informed decisions in the design of supply chain network.

کلیدواژه‌ها English

Supply chain design
Automobile tire industry
Index of value-creation
Sustainability
Metaheuristic algorithms
[1] Batty M, Axhausen KW, Giannotti F, Pozdnoukhov A, Bazzani A, Wachowicz M, et al. Smart cities of the future. The European Physical Journal Special Topics. 2012;214(1):481-518.  https://doi.org/10.1140/epjst/e2012-01703-3
[2] Barbosa-Póvoa AP, Da Silva C, Carvalho A. Opportunities and challenges in sustainable supply chain: An operations research perspective. European journal of operational research. 2018;268(2):399-431. https://doi.org/10.1016/j.ejor.2017.10.036
[3] Popovic T, Barbosa-Póvoa A, Kraslawski A, Carvalho A. Quantitative indicators for social sustainability assessment of supply chains. Journal of cleaner production. 2018;180:748-68. 2 https://doi.org/10.1016/j.jclepro.2018.01.142
[4] Mota B, Gomes MI, Carvalho A, Barbosa-Povoa AP. Sustainable supply chains: An integrated modeling approach under uncertainty. Omega. 2018;77:32-57. https://doi.org/10.1016/j.omega.2017.05.006
[5] Sabogal-De La Pava ML, Vidal-Holguín CJ, Manotas-Duque DF, Bravo-Bastidas JJ. Sustainable supply chain design considering indicators of value creation. Computers & Industrial Engineering. 2021;157:107294. https://doi.org/10.1016/j.cie.2021.107294
[6] Melo MT, Nickel S, Da Gama FS. Dynamic multi-commodity capacitated facility location: a mathematical modeling framework for strategic supply chain planning. Computers & Operations Research. 2006;33(1):181-208. https://doi.org/10.1016/j.cor.2004.07.005
[7] Melo MT, Nickel S, Saldanha-Da-Gama F. Facility location and supply chain management-A review. European journal of operational research. 2009;196(2):401-12. https://doi.org/10.1016/j.ejor.2008.05.007
[8] Amin SH, Zhang G. A multi-objective facility location model for closed-loop supply chain network under uncertain demand and return. Applied mathematical modelling. 2013;37(6):4165-76. https://doi.org/10.1016/j.apm.2012.09.039
[9] Shankar BL, Basavarajappa S, Chen JC, Kadadevaramath RS. Location and allocation decisions for multi-echelon supply chain network-A multi-objective evolutionary approach. Expert Systems with Applications. 2013;40(2):551-62. https://doi.org/10.1016/j.eswa.2012.07.065
[10] Shahabi M, Akbarinasaji S, Unnikrishnan A, James R. Integrated inventory control and facility location decisions in a multi-echelon supply chain network with hubs. Networks and Spatial Economics. 2013;13(4):497-514. https://doi.org/10.1007/s11067-013-9196-4
[11] Afshari H, Sharafi M, ElMekkawy T, Peng Q. Optimizing multi-objective dynamic facility location decisions within green distribution network design. Procedia Cirp. 2014;17:675-9. https://doi.org/10.1016/j.procir.2014.01.147
[12] Etemadnia H, Goetz SJ, Canning P, Tavallali MS. Optimal wholesale facilities location within the fruit and vegetables supply chain with bimodal transportation options: An LP-MIP heuristic approach. European Journal of Operational Research. 2015;244(2):648-61. https://doi.org/10.1016/j.ejor.2015.01.044
[13] Zhalechian M, Tavakkoli-Moghaddam R, Zahiri B, Mohammadi M. Sustainable design of a closed-loop location-routing-inventory supply chain network under mixed uncertainty. Transportation research part E: logistics and transportation review. 2016;89:182-214. https://doi.org/10.1016/j.tre.2016.02.011
[14] Kaya O, Urek B. A mixed integer nonlinear programming model and heuristic solutions for location, inventory and pricing decisions in a closed loop supply chain. Computers & Operations Research. 2016;65:93-103. https://doi.org/10.1016/j.cor.2015.07.005
[15] Martínez JCV, Fransoo JC. Green facility location. Sustainable supply chains: a research-based textbook on operations and strategy: Springer; 2016. p. 219-34. https://doi.org/10.1007/978-3-319-29791-0_9
[16] Talaei M, FARHANG MB, PISHVAEE M, BOZORGI AA. A BI-OBJECTIVE FACILITY LOCATION MODEL FOR A GREEN CLOSED-LOOP SUPPLY CHAIN NETWORK DESIGN. 2015.
[17] Amin SH, Baki F. A facility location model for global closed-loop supply chain network design. Applied Mathematical Modelling. 2017;41:316-30. https://doi.org/10.1016/j.apm.2016.08.030
[18] Srinivasan S, Khan SH. Multi-stage manufacturing/re-manufacturing facility location and allocation model under uncertain demand and return. The International Journal of Advanced Manufacturing Technology. 2018;94(5):2847-60. https://doi.org/10.1007/s00170-017-1066-7
[19] Khorasani ST, Almasifard M. The development of a green supply chain dual-objective facility by considering different levels of uncertainty. Journal of Industrial Engineering International. 2018;14(3):593-602. https://doi.org/10.1007/s40092-017-0245-3
[20] Yadegari E, Alem-Tabriz A, Zandieh M. A memetic algorithm with a novel neighborhood search and modified solution representation for closed-loop supply chain network design. Computers & Industrial Engineering. 2019;128:418-36. https://doi.org/10.1016/j.cie.2018.12.054
[21] Strong D, Kay M, Conner B, Wakefield T, Manogharan G. Hybrid manufacturing-Locating AM hubs using a two-stage facility location approach. Additive Manufacturing. 2019;25:469-76. https://doi.org/10.1016/j.addma.2018.11.027
[22] Sarker BR, Wu B, Paudel KP. Modeling and optimization of a supply chain of renewable biomass and biogas: Processing plant location. Applied Energy. 2019;239:343-55. https://doi.org/10.1016/j.apenergy.2019.01.216
[23] Saadati M, Hosseininezhad SJ. Designing a hub location model in a bagasse-based bioethanol supply chain network in Iran (case study: Iran sugar industry). Biomass and Bioenergy. 2019;122:238-56. https://doi.org/10.1016/j.biombioe.2019.01.013
[24] Delfani F, Samanipour H, Beiki H, Yumashev AV, Akhmetshin EM. A robust fuzzy optimisation for a multi-objective pharmaceutical supply chain network design problem considering reliability and delivery time. International journal of systems science: operations & logistics. 2022;9(2):155-79. https://doi.org/10.1080/23302674.2020.1862936
[25] Abbasi S, Daneshmand-Mehr M, Ghane Kanafi A. Green closed-loop supply chain network design during the coronavirus (COVID-19) pandemic: a case study in the Iranian automotive industry. Environmental Modeling & Assessment. 2023;28(1):69-103. https://doi.org/10.1007/s10666-022-09863-0
[26] Kumar A, Kumar K. An uncertain sustainable supply chain network design for regulating greenhouse gas emission and supply chain cost. Cleaner Logistics and Supply Chain. 2024;10:100142. https://doi.org/10.1016/j.clscn.2024.100142
[27] Goli A, Babaee Tirkolaee E, Golmohammadi A-M, Atan Z, Weber G-W, Ali SS. A robust optimization model to design an IoT-based sustainable supply chain network with flexibility: A. Goli et al. Central European Journal of Operations Research. 2025;33(3):1025-46. https://doi.org/10.1007/s10100-023-00870-4
[28] Saeidifar SM, Mahdavi I, Tajdin A, Javadian N. Modeling a sustainable and resilient supply chain in the automotive industry. Journal of quality engineering and management. 2025;14(4):379-406.
[29] Mohammadghasemi J, Najafi SE, Fallah M, Nabatchian MR. Presenting a robust optimization model for the design of the green loop supply chain network in the power plant by taking into account the disruption in the supply chain. Journal of decisions and operations research. 2023;8(4):1032-49.
[30] Razavinejad A, Najafi SE, Khalaj M, Pour HK. Agility of the drug supply chain considering economic and social aspects: Use of Internet of things and big data analysis. International Journal of Economic Sciences. 2026;15(1):54-84. https://doi.org/10.31181/ijes1512026214 
[31] Mozaffari, Daneshvar, Jafari K. Multi-objective optimization of sustainable reverse supply chain of municipal solid waste considering uncertainty: Robust optimization approach. Supply Chain Management. 2025; 88(27): 1-34.
[32] Saeedi M, Fathollahzadeh K, Zokaee M, Jolai F, Aghsami A. Bi-objective optimization model for biomass supply chains towards net-zero goals: Integrating queuing systems and solar panel technologies. Environment, Development and Sustainability. 2026:1-48. https://doi.org/10.1007/s10668-025-07247-4
[33] Sojoudi P, Paydar MM, Nayeri S. Designing a circular dual channel fish supply chain network considering sustainability: A case study. Computers & Industrial Engineering. 2025;203:111017. https://doi.org/10.1016/j.cie.2025.111017 
دوره 4، شماره 3 - شماره پیاپی 15
در حال انتشار
پاییز 1405
صفحه 27-52

  • تاریخ دریافت 29 فروردین 1405
  • تاریخ بازنگری 06 خرداد 1405
  • تاریخ پذیرش 11 خرداد 1405