اخبار و اعلانات
آمار
| تعداد نشریات | 36 |
| تعداد شماره‌ها | 1,227 |
| تعداد مقالات | 8,912 |
| تعداد مشاهده مقاله | 7,637,096 |
| تعداد دریافت فایل اصل مقاله | 4,549,343 |
بهینه‌سازی زنجیره تامین سبز با لحاظ فناوری مورد استفاده در تولید تحت شرایط عدم قطعیت | ||
| مدیریت زنجیره تأمین | ||
| دوره 25، شماره 81، اسفند 1402، صفحه 77-85 اصل مقاله (904.05 K) | ||
| نوع مقاله: پژوهشی | ||
| نویسنده | ||
| ملیحه ابراهیمی* | ||
| استادیار، گروه مهندسی صنایع، دانشکده فنی مهندسی، دانشگاه کوثر بجنورد | ||
| تاریخ دریافت: 31 خرداد 1402، تاریخ بازنگری: 29 آبان 1402، تاریخ پذیرش: 18 بهمن 1402 | ||
| چکیده | ||
| امروزه با توجه به افزایش جمعیت، رشد فناوری و افزایش انتشار گازهای گلخانه‌ای، کاهش آلودگی‌های زیست‌محیطی ناشی از تولید محصولات و حمل و نقل آنها بسیار حائز اهمیت است. در این مقاله یک مدل جدید چند هدفه زنجیره تامین سبز سه سطحی ارائه شده است که متشکل از تامین‌کنندگان، تولیدکنندگان و مشتریان است. هدف اصلی این مقاله که وجه تمایز مدل ارائه شده با مدل‌های قبلی می‌باشد، در نظر گرفتن سه هدف حداکثرسازی سود (کاهش هزینه)، کاهش آلودگی زیست محیطی و افزایش کیفیت به طور همزمان در زنجیره تامین سبز می باشد. البته در نظر گرفتن فناوری و هزینه، آلودگی و کیفیت متاثر از آن نیز وجه تمایز دیگر این مدل می‌باشد. با توجه به اینکه در دنیای واقعی اطلاعات به صورت قطعی در دسترس نیستند، بنابراین از رویکرد غیرقطعی استفاده خواهد شد. در این مطالعه نیز پارامترهای مربوط به آلودگی‌های زیست محیطی و کیفیت محصول غیرقطعی و به صورت عدد فازی لحاظ شده است. سپس با استفاده از روش وزن‌دهی به اهداف و روش LP-metric، چند هدفه به مدل تک هدفه تبدیل شده و با استفاده از نرم افزار گمز مورد حل قرار گرفت. تحلیل حساسیت نیز بر روی برخی پارامترها انجام شده است. نتایج بدست آمده، حساسیت بیشتر مدل ارائه شده، به تغییرات تقاضا را نشان می‌دهد. از نظر مدیریتی، این مقاله می‌تواند به عنوان یک راهنمای مناسب برای طراحی شبکه زنجیره تأمین سبز با در نظر گرفتن تأثیرات فاکتورهای تکنولوژی، سود، هزینه و اثرات زیست محیطی در شرایط عدم قطعیت باشد. | ||
| کلیدواژه‌ها | ||
| زنجیره تامین؛ تکنولوژی؛ کیفیت محصول؛ برنامه ریزی فازی | ||
| عنوان مقاله [English] | ||
| Optimizing the Green Supply Chain Considering Technology which Used in Production Under Uncertainty | ||
| نویسندگان [English] | ||
| malihe ebrahimi | ||
| department of industrial engineering, college of basic science and engineering, kosar university of bojnord, iran. | ||
| چکیده [English] | ||
| Nowdays, due to the increase in population, the growth of technology and the enhancement in greenhouse gas emissions, it is very important to reduce the environmental pollution of manufacturing of products and the transportations. This article presents a new three level green supply chain model that consist of suppliers, manufacturers and customers. The novelty of this lecture is considering three objects simultaneously. Also, considering the technology, pollution and quality is the other novelties of this model. Due to the fact that in the real world information is not available, the non-deterministic approach will be used environmental pollution parameters and product quality parameters is considered in non-deterministic, the form of fuzzy numbers. The weighting the goals and LP-metric method are used to convert the multi-objective model to single- objective model which solving by GAMS software. Sensitivity analysis is done on some parameters. The obtained results show the greeter sensitivity of the new model to changes of demand. From of managerial point of view, this article can serve as a suitable guide for green supply chain network design, considering the effects of technology, profit, cost, and environmental factors under uncertainty. | ||
| کلیدواژه‌ها [English] | ||
| Supply chain, technology, product quality, fuzzy planing | ||
| مراجع | ||
|
[1] R. Sadegi Rad and N. Nahavandi, “A novel multi-objective optimization model for integrated problem of green closed-loop supply chain network design and quantity discount”, Journal of Cleaner Production, vol. 196, pp. 1549-1565, 2018. DOI: 10.1016/j.jclepro.2018.06.034 [2] R. Ma, L. Yao, M. Jin, P. Ren, and Z. LV, “Robust environmental closed-loop supply chain design under uncertainty”, Chaos, Solitons & Fractals, vol. 89, pp. 195-202, 2016. DOI: 10.1016/j.chaos.2015.10.028 [3] A. Mahmoudi, M. Abedian, and D. Shishebori, “The Dual-Channel Green Supply Chain Performance Under Government Monitoring: A Game Theoretic Approach”, Advances in Industrial Engineering, vol. 54, pp. 423-446, 2020. DOI: 10.22059/jieng.2021.325645.1781 [4] M. Arabi, and M. R. Gholamian, “Sustainable Supply Chain Network Design with PriceBased Demand Considering Sound and Dust Pollutions: A Case Study”, Advances in Industrial Engineering, vol. 55(3) pp. 285-306, 2021. DOI: 10.22059/AIE.2021.331646.1809. [5] M. L. Tseng, M. Shamimul Islam N. Karia, F. A. Fauzi, and S. Afrin, “A literature review on green supply chain management: Trents and future challenges”, Resources, Conservation and Recycling, vol. 141, pp. 145-162, 2019. DOI: 10.1016/j.resconrec.2018.10.009. [6] S. Badi, and N. Murtagh, “Green supply chain management in construction: a systematic literature review and future research agenda”, Journal of Cleaner Production, vol. 223, pp. 312-322, 2019. DOI: 10.1016/j.jclepro.2019.03.132. [7] C. Haiyun, H. Zhixiong, S. Yuksel, and H. Dincer, “Analysis of innovation strategies for green supply chain management in the energy industry using the QFD-based hybrid interval valued intuitionistic fuzzy decision approach”, Renewable and Sustainable Energy Reviews, vol. 143, pp. 1-17, 2021. DOI: 10.1016/j.rser.2021.110844. [8] S. Benzidia, N. Makaoui, and O. Bentahar, “The impact of big data analytics and artificial intelligence on green supply chain process integration and hospital environmental performance”, Technological Forecasting and Social Change, vol. 165, pp. 1-13, 2021. DOI: 10.1016/j.techfore.2020.120557. [9] A. M. Bashokouh, and K.V. Ebrahimi, “Investigating the Impact of Institutional Pressure and Market Orientation on the Green Supply Method and Competitive Advantage with the Mediating Role of Managerial Commitment (Case Study: Textile Industry)”, Iranian Journal of Supply Chain Management, vol. 25(78), PP. 9-21, 2023. (In Persian) [10] A. Lotfi, M. Gholami, M. Lotfi Jalalabadi, A. Saadatian Asl, “Analyzing the Factors Affecting the Green Supply Chain Management in Logistic Systems”, Iranian Journal of Supply Chain Management, vol. 19, pp. 18-31, 2017. (In Persian) [11] M. Seifbarghy, M. Soleimani, and M. Jabbari, “Comparing Multi-Objective Meta-Heuristics for Multi- Commodity Supply Chain Design Problem with Partial Coverage”, Advances in Industrial Engineering, vol. 54(4), pp. 365-379, 2020. DOI: 10.22059/JIENG.2021.325287.1775. [12] F. Salehi, Y. Allahyari Emamzadeh, A. E. Mirzapour, S. M. J. hashem, and R. Shafiei Aghdam, “An L-Shaped Method to Solve a Stochastic Blood Supply Chain Network Design Problem in a Natural Disaster”, Advances in Industrial Engineering, vol. 55(1) pp. 47-68, 2021. DOI: 10.22059/jieng.2021.325375.1776. [13] A. Arasteh, “Optimizing Inventory Management Costs in Supply Chains by Determining Safety Stock Placement”, Journal of Optimization in Industrial Engineering, vol. 15(1), pp.1-15, 2022. [14] S. Jalali, M. Seifbarghy, and S. T. Akhavan Niaki, “A Risk-averse Inventory-based Supply Chain Protection Problem with Adapted Stochastic Measures under Intentional Facility Disruptions: Decomposition and Hybrid Algorithms”, Journal of Optimization in Industrial Engineering, vol. 13(2), pp. 211- 226, 2020. DOI: 10.22094/JOIE.2019.1868275.1654. [15] M. A. Ardakani, “A Multi-Objective Supply Chain Configuration for the Oil Industry under Uncertainty”, Advances in Industrial Engineering, vol. 56(1), pp. 15-41, 2022. DOI: 10.22059/AIE.2022.335295.1816. [16] D. Mohamadi Janaki, H. Izadbakhsh, S.M. Hatefi, M. Yavari, and M. Khalili Samani, “Supply Chain Network Performance Measurement and Improvement Using DEA and SCOR Models in Dynamic Conditions”, Advances in Industrial Engineering, vol. 56(2) pp. 163-197, 2022. DOI: 10.22059/AIE.2022.341621.1833. [17] A. Noorbakhsh, R. Soltani, M. Asadi Mafi, “Supply Chain and Predictability of Return”, Advances in Industrial Engineering, vol. 55(4), pp. 323- 333, 2021. DOI: 10.22059/aie.2021.330003.1803. [18] A. Shamekhi Amiri, and N. Manavizadeh, “Evaluating Barriers of Block chain-Based Platforms Implementation for Subsidized Foods Supply Chains: A Hybrid Approach Based on BWM and WINGS Methods. Advances in Industrial Engineering”, vol. 56(2), pp. 199-214, 2022. DOI: 10.22059/AIE.2022.341963.1834. [19] R. Kwesi Ansaha, and G. Ayoka Akipelub, “Integrating the Supply Chain to Excel: The Moderating Role of Competitive Advantage”, International Journal of Supply and Operations Management, vol. 8(4), pp. 401-415, 2021. [20] T. Shahedi, A. Aghsami, and M. Rabbani, “Designing a green closed-loop supply chain network for the automotive tire industry under uncertainty”, Journal of Industrial and Systems Engineering, vol. 13(4), pp. 226-261, 2021. [21] V. Razmjooei, I. Mahdavi, and M. M. Paydar, “A Fuzzy Bi-objective Optimization Algorithm Model to Design a Reverse Supply Chain Network: A Cuckoo Optimization Algorithm”, International Journal of Supply and Operations Management, vol. 9(3), pp. 360-378, 2022. [22] D. Feizollahi, and V. Sharfi, “Development of a Closed-Loop Supply Chain Mathematical Model with Demand Constraints and Fuzzy Supplier Capacity and Solving it with Meta-Heuristic Algorithms”, Iranian Journal of Supply Chain Management, vol. 25(79), pp.17-38, 2023. Dor: 20.1001.1.20089198.1402.25.79.2.6 (In Persian) [23] M. Ebrahimi, and R. Tavakkoli-Moghaddam,“Benders decomposition algorithm for a green closed-loop supply chain under a build-to-order environment”, Journal of Industrial and Systems Engineering, vol. 13, pp. 102-111, 2020. [24] A. Goli, and A. M. Golmohammadi, “Multi-objective Optimization of Location and Distribution in a Closed-loop Supply Chain by Considering Market Share in Competitive Conditions”, International Journal of Supply and Operations Management, vol. 9(4), pp. 483-495, 2022. DOI: 10.22034/IJSOM.2021.109265.2285. | ||
|
آمار تعداد مشاهده مقاله: 212 تعداد دریافت فایل اصل مقاله: 271 |
||