مدل چند هدفه فازی شبکه زنجیره تامین حلقه بسته در صنعت خودرو با رویکرد مدیریت شهری

الموضوعات : مطالعات مدیریت شهری

سعید امین پور ¹ , علیرضا ایرج پور ² , مهدی یزدانی ³

1 - دانشجوی دکتری مدیریت صنعتی، واحد قزوین، دانشگاه آزاد اسلامی، قزوین، ایران. (نویسنده مسئول) [e-mail]
2 - استادیار گروه مدیریت صنعتی ، واحد قزوین، دانشگاه آزاد اسلامی، قزوین، ایران
3 - استادیار گروه مهندسی صنایع ، واحد قزوین، دانشگاه آزاد اسلامی، قزوین، ایران

تاريخ الإرسال : 29 الأربعاء , صفر, 1443 تاريخ التأكيد : 01 الأحد , جمادى الأولى, 1443 تاريخ الإصدار : 17 الإثنين , ربيع الثاني, 1443

الکلمات المفتاحية: شبکه زنجیره تامین حلقه بسته, صنعت خودرو, بازده انرژی و زمان, مدیریت شهری,

ملخص المقالة :

مقدمه و هدف پژوهش: هدف تحقیق حاضر طراحی مدل چند هدفه فازی شبکه زنجیره تامین حلقه بسته در صنعت خودرو با رویکرد مدیریت شهری می‌باشد. تولید خودرو فرآیندی پیچیده و پرانرژی است که مقدار قابل توجهی مواد اولیه و آب را مصرف می‌کند. برای ادامه رقابت، تولیدکنندگان تجهیزات اصلی خودرو باید با بهبود مستمر روند تولید خود و هدایت تولید گازهای گلخانه ای با میزان کم کربن و افزایش پایداری، برای کیفیت بهتر محصول تلاش کنند. در همین راستا شبکه های زنجیره تامین معکوس و زنجیره های حلقه بسته دارای ویژگی های خاصی هستند که در صنعت مورد بررسی بسیار مفید می‌باشد. روش پژوهش: در تحقیق حاضر به منظور رسیدن به اهداف تحقیق از روش تحقیق کمی استفاده خواهد شد و براساس هدف به صورت کاربردی تعریف شده است. در این مطالعه، از روش MOPSO برای تسهیل اجرای آن و توانایی آن در ارائه هم‌گرایی خوب و همچنین الگوریتم ژنتیک NSGA II استفاده می‌کنیم. یافته‌ها: در بررسی یافته های الگوریتم های پیشنهادی مشخص شد که میانگین خطای حاصل از این الگوریتم‌ها کمتر از 04/0 است. همچنین نتایج نشان می‌دهد که الگوریتم های پیشنهادی کارایی لازم را در حل این مسائل دارند نتیجه گیری:نتایج قابل توجه مدل خود را چنین ذکر می‌کنیم: (1) شبکه ی حلقه بسته ی کارآمدی که مزایای اقتصادی با توجه به در نظر گرفتن ارزش زمان را با توجه به بازیافت محصول فرسوده نشان می‌دهد. (2) این توانایی را دارد که ظرفیت را برای دستیابی به حداکثر مزایا از نظر ارزش هزینه و نیز چشم انداز محیطی نشان دهد که چه ظرفیتی را باید حفظ کند.

المصادر:

 Alomar, M., & Pasek, z. J. (2014). Linking supply chain strategy and processes to performance improvement Variety Management in Manufacturing. Proceedings of the 47th CIRP Conference on Manufacturing Systems, 17, 6. doi:https://doi.org/10.1016/j.procir.2014.01.144

Amin, S. H., & Baki, F. (2017). A facility location model for global closed-loop supply chain network design. Applied Mathematical Modelling, 41. doi:http://dx.doi.org/10.1016/j.apm.2016.08.030

Armin Jabbarzadeh , M. H., Amir Khosrojerdi. (2018). Closed-loop supply chain network design under disruption risks: A robust approach with real world application. Computers & Industrial Engineering, 118, 178. doi:https://doi.org/10.1016/j.cie.2017.12.025

Ashfari, H., Sharifi, M., ElMekkawy, T. Y., & Peng, Q. (2014). Facility Location Decisions Within Integrated Forward/Reverse Logistics under Uncertainty. Procedia CIRP, 17, 5. doi: 10.1016/j.procir.2014.01.092

Barbosa-Póvoa, A. P., Silva, C., & Carvalho, A. (2018). Opportunities and challenges in sustainable supply chain: An operations research perspective. European Journal of Operational Research, 268(2), 32. doi:https://doi.org/10.1016/j.ejor.2017.10.036

Bavarsad, Belqis; Rezaei Jarivand, Batool; Rahimi, Farajollah; Sinaei, Hassan Ali (2016) "Study of the Alignment of Supply Chain Strategies and Information System Strategies on Supply Chain Management Performance (Case Study: Manufacturing Companies in Khuzestan Province)" Journal of Technology Management Tehran University Information, Winter 2016, No. 29 (In Persian)

Cai, X., Gao, L., & Li, F. (2019). Sequential approximation optimization assisted particle swarm optimization for expensive problems. Applied Soft Computing Journal, 83. doi:https://doi.org/10.1016/j.asoc.2019.105659

Chen, Y.-W., Wang, L.-C., Wang, A., & Chen, T.-L. (2017). A particle swarm approach for optimizing a multi-stage closed loop supply chain for the solar cell industry. Robotics andComputer-Integrated Manufacturing, 43, 12. doi:http://dx.doi.org/10.1016/j.rcim.2015.10.006

Dekker, R., Fleischmann, M., & Inderfurth, K. (2004). Quantitative Models for Closed-Loop Supply Chains: Springer-Verlag Berlin Heidelberg.

Farrokh, M., Azar, A., Jandaghi, G., & Ahmadi, E. (2017). A novel robust fuzzy stochastic programming for closed loop supply chain network design under hybrid uncertainty. Fuzzy SetsandSystems, 3, 23. doi:http://dx.doi.org/10.1016/j.fss.2017.03.019

Fathollahi-Fard, A. M., Hajiaghaei-Keshteli, M., & Mirjalili, S. (2018). Multi-objective stochastic closed-loop supply chain network designwith social considerations. Applied Soft Computing, 71, 20. doi:https://doi.org/10.1016/j.asoc.2018.07.025

Fallah, H., Eskandari, H., Zgardi, S. Chaharsooqi, S. (1396). Presenting a two-level model of closed-loop supply chain network design in conditions of uncertainty and inter-chain competition: a solution with the Banders analysis approach. Journal of Modeling in Engineering, 49, 15. (In Persian

Fleischmann, M., Beullens, P., Bloemhof-Ruwaard, J., & Wassenhove, L. (2001). The impact of product recovery on logistics network design. Production and Operations Management,

Giovanni, P. D. (2018). A joint maximization incentive in closed-loop supply chains with competing retailers: The case of spent-battery recycling. European Journal of Operational Research, 1. doi:10.1016/j.ejor.2018.01.003

Haddadsisakht, A., & Ryan, S. M. (2018). Closed-loop supply chain network design with multiple transportation modes under stochastic demand and uncertain carbon tax. International Journal of Production Economics, 195, 13. doi:https://doi.org/10.1016/j.ijpe.2017.09.009

Hajian, Sima; Afshar Kazemi, Mohammad Ali; Seyed Hosseini, Seyed Mohammad; Tolouei Ashlaghi, Abbas (2019), Presenting a Multi-Objective Model for the Problem of Location-Routing-Inventory in the Multi-Periodic Green Ring Supply Chain Network and Multi-Product for Perishable Goods, Industrial Management, 11 (1), 83 - 110(In Persian)

Hassanzadeh, A. S., & Zhang, G. (2013). A multi-objective facility location model for closed-loop supply chain network under uncertain demand and return. Applied Mathematical Modelling, 37, 12. doi:http://dx.doi.org/10.1016/j.apm.2012.09.039

Hsiao-Fan Wang , H.-W. (2010). A closed-looplogisticmodelwithaspanning-treebasedgeneticalgorithm. Computers &OperationsResearch, 37, 13. doi:10.1016/j.cor.2009.06.001

Jabbarzadeh, A., Haughton, M., & Khosrojerdi, A. (2018a). Closed-loop supply chain network design under disruption risks: A robust approach with real world application. Computers & Industerial Engineering, 116, 13. doi:https://doi.org/10.1016/j.cie.2017.12.025

Jabbarzadeh, A., Haughton, M., & Khosrojerdi, A. (2018b). Closed-loop supply chain network design under disruption risks: A robust approach with real world application. Computers & Industrial Engineering, 116, 14. doi:https://doi.org/10.1016/j.cie.2017.12.025

Jawad, H., Jaber, M., & Nuwayhid, R. (2018). Improving supply chain sustainability using exergy analysis. European Journal of Operational Research, 269, 13. doi:https://doi.org/10.1016/j.ejor.2017.10.007

Kadambala, D. K., Subramanian , N., Tiwari , M. K., Abdulrahman , M., & Liu, C. (2017). Closed loop supply chain networks: Designs for energy and time value efficiency. Int. J.ProductionEconomics, 183, 382. doi:http://dx.doi.org/10.1016/j.ijpe.2016.02.004

Kaya, O., & Urek, B. (2016). A mixed integer nonlinearprogramming model and heuristic solutions for location , inventory and pricing decisions in a closed loop supply chain. Computers &OperationsResearch, 65, 10.

Liao, S.-H., Hu, D.-C., & Ding, L.-W. (2017). Assessing the influence of supply chain collaboration value innovation, supply chain capability and competitive advantage in Taiwan's networking communication industry. International Journal of Production Economics, 191, 10.

Lu, Z., & Bostel, N. (2007). A facility location model for logistics systems including reverse flows: The case of remanufacturing activities. Computers & Operations Research, 34, 25.

Özceylan, E., Demirel, N., Çetinkaya, C., & Demirel, E. (2017). A closed-loop supply chain network design for automotive industry in Turkey. Computers & Industrial Engineering, 113,

Nambajemariya, F. and Wang, Y. (2021) Excavation of the Internet of Things in Urban Areas Based on an Intelligent Transportation Management System. Advances in Internet of Things, 11, 113-122. doi: 10.4236/ait.2021.113008.

22. Sasikumar , A. N. H. (2011). Integration of closed loop distribution supply chain network and 3PRLP selection for the case of battery recycling. International Journal of Production Research, 49, 22. doi:https://doi.org/10.1080/00207541003794876

Pishvaee, M. S., Kianfar, K., & Karimi, B.. (2010). Reverse logistics network design using simulated annealing. The International Journal of Advanced Manufacturing Technology, 47, 12. doi:https://doi.org/10.1007/s00170-009-2194-5

Shakourloo, A., Kazemi, A., & Javad, M. O. M. (2016). A new model for more effective supplier selection and remanufacturing process in a closed-loop supply chain. Applied Mathematical Modelling, 40, 17. doi:http://dx.doi.org/10.1016/j.apm.2016.06.039

Soleimani, H., Govindan, K., Saghafi, H., & Jafari, H. (2017). Fuzzy multi-objective sustainable and green closed-loop supply chain network design. Computers & Industrial Engineering, 109, 191. doi:http://dx.doi.org/10.1016/j.cie.2017.04.038

Taleizadeh, A. A., Haghighi, F., & Niaki, S. T. A. (2019). Modeling and solving a sustainable closed loop supply chain problem with pricing decisions and discounts on returned products. Journal of Cleaner Production, 207, 18. doi:https://doi.org/10.1016/j.jclepro.2018.09.198

Ekhtiari, M., Zandieh, M., Alem Tabriz, A., & Rabieh, M. (2019). Proposing a Bi-level Programming Model for Multi-echelon Supply Chain with an Emphasis on Reliability in Uncertainty. Industrial Management Journal, 11(2), 177-206. (in Persian)

Giampieri, Alessandro; Ling-Chin, Janie; Ma, Zhiwei; Smallbone, Andrew; Roskilly, Antony (2020) “A review of the current automotive manufacturing practice from an energy perspective” Applied Energy 261 (2020) 114074

Jabbarzadeh, Armin; Haughton, Michael; Khosrojerdi, Amir (2018) “Closed-loop supply chain network design under disruption risks: A robust approach with real world application” Computers & Industerial Engineering, Volume 116 , 178- 191 ,

Soleimani, Hamed; Govindan Kannan (2015) “A hybrid particle swarm optimization and genetic algorithm for closed-loop supply chain network design in large-scale networks” Applied Mathematical Modelling, Volume 39, 3990-4010,

Tarokh, J., Mahsa, A. G., & Shohreh, T. (2014). General model for optimizing reverse logistics network design under uncertainty. Specialized Journal of Industrial Engineering, 2, 15. (In Persian)

Yavari, Mohammad., Geraeli, Mohaddase., 2019. Heuristic method for robust optimization model for green closed-loop supply chain network design of perishable goods. J. Clean. Prod. 226, 282e305

Zhou, X., & Zhou, Y. (2015). Designing a multi-echelon reverse logistics operation and network:A case study of office paper in Beijing. Resources, Conservation and Recycling, 100, 12. doi:http://dx.doi.org/10.1016/j.resconrec.2015.04.009