ارائه یک مدل بهینه‌سازی لجستیک معکوس جهت کاهش اثرات زیست‌محیطی مبتنی بر مدیریت ضایعات
محورهای موضوعی : مدیریت صنعتیمهتا کاکویی 1 , محمود مدیری 2 , قنبر عباسپور اسفدن 3
1 - گروه مديريت صنعتي، واحد تهران جنوب، دانشگاه آزاد اسلامی، تهران، ایران
2 - دانشيار گروه مدیریت صنعتی، واحد تهران جنوب، دانشگاه آزاد اسلامی، تهران، ایران(نويسنده مسئول)
3 - استاديار گروه مدیریت صنعتی، واحد تهران جنوب، دانشگاه آزاد اسلامی، تهران، ایران
کلید واژه: بهینه‌سازی لجستیک معکوس, اثرات زیست محیطی, مدیریت ضایعات,
چکیده مقاله :
امروزه افزایش جمعیت و رشد سریع شهرنشینی، افزایش سطح زندگی اجتماعی، تولید زباله های جامد را در جهان به میزان قابل توجهی تسریع کرده است. ضایعات جامد تبدیل به یکی از مهمترین مسائل زیست محیطی در سطح جهان شده است. بنابراین، سیستم مدیریت ضایعات و لجستیک معکوس (RL) اخیراً به دلیل ترکیبی از عوامل محیطی، اقتصادی و اجتماعی مورد توجه قرار گرفته است. بنابراین برای جلوگیری از تخریب بیشتر محیط زیست ضروری است. مدیریت ضایعات شامل جمع آوری، انتقال، پاکسازی، بازیافت و دفع پسماندهاست. این پژوهش شامل یک شبکه لجستیک معکوس یازده سطحی و چند محصولی است که قابلیت حمایت از انواع صنایعی را دارد که محصولاتشان در دوران پایانی عمرخود قرار دارند. این تحقیق به طراحی شبکه لجستیک معکوسی است که کلیه ضایعات را در یک محل جمع‌آوری و بر اساس نیاز کارخانجات (از لحاظ جنس و ماهیت ضایعات و ...) آن‌ها را تفکیک و به مقصد مورد نظر جهت بازیافت ارسال می‌کند. در این پژوهش مدل ریاضی مختلط جهت کاهش هزینه‌های کل سیستم ارائه شده است. تعداد مراکزتسهیلات، تعداد محصولات و قطعاتی که باید از یک مرکز به مرکز دیگر ارسال شوند، میزان انتشار CO2 و هزینه کل مدل مشخص شده است.
Solid waste has become one of the most critical environmental issues in the world. Therefore, a waste management system to prevent further destruction of the environment is essential. Waste management includes collection, transport, cleaning, recycling, and disposal of the wastes. In recent years, due to environmental concerns, manufacturers have been forced to offer environmentally friendly products. So, the area of reverse logistics (RL) has recently received considerable attention, due to a combination of environmental, economic, and social factors. In this research, the design of a multi-product and eleven-level reverse logistics network is conducted, which collects all the waste in one place and separates them according to the needs of the factories (in terms of the type and material of the waste, etc.) and sends them to the intended destination. This model can support all kinds of industries in which the revival of recycling and destruction of products. This study provides a mixed integer mathematical model to reduce the costs of the whole system. The number of centers, the number of products and parts that should be sent from one center to another, the amount of CO2 emissions, and the total cost of the model were determined. Finally, the sensitivity analysis was done on the parameters of the model. The model was validated by changing the input data in two different cases.
Abu-Qdais, H. M. Al-Ghazo, and E. Al-Ghazo, Statistical analysis and characteristics of hospital medical waste under novel Coronavirus outbreak. Global Journal of Environmental Science and Management, 2020. 6(Special Issue (Covid-19)): p. 21-30. https://doi.org/10.22034/GJESM.2019.06.SI.03
Abdallah, T., A. Diabat, and D. Simchi-Levi. A carbon sensitive supply chain network problem with green procurement. in The 40th International Conference on Computers & Indutrial Engineering. 2010. IEEE
Bautista, J. and J. Pereira, Modeling the problem of locating collection areas for urban waste management. An application to the metropolitan area of Barcelona. Omega, 2006. 34(6): p. 617-629. https://doi.org/10.1016/j.omega.2005.01.013
Das, S. and B.K. Bhattacharyya, Optimization of municipal solid waste collection and transportation routes. Waste Management, 2015. 43: p. 9-18. https://doi.org/10.1016/j.wasman.2015.06.033
Gharibi, K. and S. Abdollahzadeh, A mixed-integer linear programming approach for circular economy-led closed-loop supply chains in green reverse logistics network design under uncertainty. Journal of Enterprise Information Management, 2021. https://doi.org/10.1108/JEIM-11-2020-0472
Govindan, K. et al. Fuzzy multi-objective approach for optimal selection of suppliers and transportation decisions in an eco-efficient closed loop supply chain network. Journal of Cleaner Production, 2017. 165: p. 1598-1619. https://doi.org/10.1016/j.jclepro.2017.06.180
Govindan, K. et al. Medical waste management during coronavirus disease 2019 (COVID-19) outbreak: A mathematical programming model. Computers & Industrial Engineering, 2021. 162: p. 107668. https://doi.org/10.1016/j.cie.2021.107668
Hashemi, S.E. A fuzzy multi-objective optimization model for a sustainable reverse logistics network design of municipal waste-collecting considering the reduction of emissions. Journal of Cleaner Production, 2021. 318: p. 128577. https://doi.org/10.1016/j.jclepro.2021.128577
Homayouni, Z. and M.S. Pishvaee, A bi-objective robust optimization model for hazardous hospital waste collection and disposal network design problem. Journal of Material Cycles and Waste Management, 2020. 22: p. 1965-1984 https://doi.org/10.1007/s10163-020-01081-8
Jaunich, M.K. et al. Life-cycle modeling framework for electronic waste recovery and recycling processes. Resources, Conservation and Recycling, 2020. 161: p. 104841 https://doi.org/10.1016/j.resconrec.2020.104841
Kargar, S. M. Pourmehdi, and M.M. Paydar, Reverse logistics network design for medical waste management in the epidemic outbreak of the novel coronavirus (COVID-19). Science of the Total Environment, 2020. 746: p. 141183. https://doi.org/10.1016/j.scitotenv.2020.141183
Kannan, G., P. Sasikumar, and K. Devika, A genetic algorithm approach for solving a closed loop supply chain model: A case of battery recycling. Applied mathematical modelling, 2010. 34(3): p. 655-670
Kilic, H.S. U. Cebeci, and M.B. Ayhan, Reverse logistics system design for the waste of electrical and electronic equipment (WEEE) in Turkey. Resources, Conservation and Recycling, 2015. 95: p. 120-132. https://doi.org/10.1016/j.resconrec.2014.12.010
Lee, C. et al. A mathematical model for municipal solid waste management–A case study in Hong Kong. Waste management, 2016. 58: p. 430-441 https://doi.org/10.1016/j.wasman.2016.06.017
Li, G. J. Liu, and A. Giordano, Robust optimization of construction waste disposal facility location considering uncertain factors. Journal of Cleaner Production, 2022. 353: p. 131455 https://doi.org/10.1016/j.jclepro.2022.131455.
Nanaki, E.A. C.J. Koroneos, and G.A. Xydis, Environmental impact assessment of electricity production from lignite. Environmental Progress & Sustainable Energy, 2016. 35(6): p. 1868-1875 https://doi.org/10.1002/ep.12427.
Ottoni, M. P. Dias, and L.H. Xavier, A circular approach to the e-waste valorization through urban mining in Rio de Janeiro, Brazil. Journal of Cleaner Production, 2020. 261: p. 120990 https://doi.org/10.1016/j.jclepro.2020.120990
Pishvaee, M.S., J. Razmi, and S.A. Torabi, Robust possibilistic programming for socially responsible supply chain network design: A new approach. Fuzzy sets and systems, 2012. 206: p. 1-20. https://doi.org/10.1016/j.fss.2012.04.010
Yu, H., et al., A stochastic network design problem for hazardous waste management. Journal of cleaner production, 2020. 277: p. 123566 https://doi.org/10.1016/j.jclepro.2020.123566
Xiao, Z., et al., Location-allocation problem of reverse logistics for end-of-life vehicles based on the measurement of carbon emissions. Computers & Industrial Engineering, 2019. 127: p. 169-181. https://doi.org/10.1016/j.cie.2018.12.012
Zarbakhshnia, N., et al., A novel multi-objective model for green forward and reverse logistics network design. Journal of cleaner production, 2019. 208: p. 1304-1316. https://doi.org/10.1016/j.jclepro.2018.10.138(
