طراحی پایدار زنجیره تأمین تولید اتانول زیستی از نیشکر
محورهای موضوعی : مدیریت دانشهادی صاحبی 1 * , هانی گیلانی 2
1 - دانشگاه علم و صنعت ایران
2 - دانشگاه علم وصنعت
کلید واژه: زنجیره تأمین زنجیره تأمین پایدار اتانول زیستی برنامه ریزی سناریو محور اختلال,
چکیده مقاله :
گراني و خطر پايان يافتن سوخت هاي فسيلي و شدت آلودگي هوا امروزه کلان شهرها را به شدت تهديد مي کند و از این رو توجه به انرژی های تجدید پذیر امری اجتناب ناپذیر است. در این مقاله یک زنجیره تأمین سه سطحی تولید اتانول زیستی با سه هدف ماکزیمم کردن سود، کاهش اثرات زیست محیطی و ماکزیمم کردن اثرات اجتماعی ارائه گردید است که برای حل آن از روش اپسیلون- محدودیت استفاده شده است. در سطح سوم چندین بازار مصرف وجود دارد که به ارضا کردن تقاضای مشتری نهایی می پردازند. نوع خوراک در نظر گرفته شده نیشکر است که می توان از آن ها برای تولید اتانول زیستی استفاده کرد. افق برنامه ریزی چند دوره ای با فرض این که ارتباط سطوح زنجیره با یکدیگر ممکن است دچار اختلال شوند. در نهایت با یک مطالعه موردی در منطقه جنوب شرقی ایران کارکرد مدل نشان داده شده است.
High cost, the risk of ending fossil fuels and pollution severely threatens metropolitan areas today and therefore paying attention to renewable energies is inevitable. This paper presents a three-level supply chain of bioethanol production with the three objectives of maximizing profit, reducing environmental impacts and maximizing social impacts, using the Epsilon-constraint method for optimization. On the third level, there are several consumer markets that satisfy end-customer demand. The type of feedstock intended is sugarcane, which can be used to produce bioethanol. The planning horizon of the model is multi-period, and the relationship of chain levels to each other may be disrupted. Finally, a case study in the Southwest region of Iran demonstrates the function of the model.
1.Shabani, N. and T. Sowlati, A hybrid multi-stage stochastic programming-robust optimization model for maximizing the supply chain of a forest-based biomass power plant considering uncertainties. Journal of Cleaner Production, 2016. 112: p. 3285-3293.
2. Andersen, F., et al., Optimal design and planning of biodiesel supply chain with land competition. Computers & Chemical Engineering, 2012. 47: p. 170-182.
3. Huang, Y., Y. Fan, and C.-W. Chen, An integrated biofuel supply chain to cope with feedstock seasonality and uncertainty. Transportation Science, 2014. 48(4): p. 540-554.
4. Sharma, B., et al., Scenario optimization modeling approach for design and management of biomass-to-biorefinery supply chain system. Bioresource technology, 2013. 150: p. 163-171.
5. Ng, W.P.Q., H.L. Lam, and S. Yusup, Supply network synthesis on rubber seed oil utilisation as potential biofuel feedstock. Energy, 2013. 55: p. 82-88.
6. Leduc, S., et al., Location of a biomass based methanol production plant: a dynamic problem in northern Sweden. Applied Energy, 2010. 87(1): p. 68-75.
7. Duarte, A., W. Sarache, and Y. Costa, Biofuel supply chain design from Coffee Cut Stem under environmental analysis. Energy, 2016. 100: p. 321-331.
8. Marufuzzaman, M., S.D. Ekşioğlu, and R. Hernandez, Environmentally friendly supply chain planning and design for biodiesel production via wastewater sludge. Transportation Science, 2014. 48(4): p. 555-574.
9. Sharifzadeh, M., M.C. Garcia, and N. Shah, Supply chain network design and operation: Systematic decision-making for centralized, distributed, and mobile biofuel production using mixed integer linear programming (MILP) under uncertainty. Biomass and Bioenergy, 2015. 81: p. 401-414.
10. Zhang, Y. and M.M. Wright, Product selection and supply chain optimization for fast pyrolysis and biorefinery system. Industrial & Engineering Chemistry Research, 2014. 53(51): p. 19987-19999.
11. You, F. and B. Wang, Life cycle optimization of biomass-to-liquid supply chains with distributed–centralized processing networks. Industrial & Engineering Chemistry Research, 2011. 50(17): p. 10102-10127.
12. Marufuzzaman, M., et al., Supply chain design and management for syngas production. ACS Sustainable Chemistry & Engineering, 2016. 4(3): p. 890-900.
13. Li, Q. and G. Hu, Supply chain design under uncertainty for advanced biofuel production based on bio-oil gasification. Energy, 2014. 74: p. 576-584.
14. Marvin, W.A., et al., Economic optimization of a lignocellulosic biomass-to-ethanol supply chain. Chemical Engineering Science, 2012. 67(1): p. 68-79.
15. Corsano, G., A.R. Vecchietti, and J.M. Montagna, Optimal design for sustainable bioethanol supply chain considering detailed plant performance model. Computers & Chemical Engineering, 2011. 35(8): p. 1384-1398.
16. Osmani, A. and J. Zhang, Stochastic optimization of a multi-feedstock lignocellulosic-based bioethanol supply chain under multiple uncertainties. Energy, 2013. 59: p. 157-172.
17. Gonela, V., J. Zhang, and A. Osmani, Stochastic optimization of sustainable industrial symbiosis based hybrid generation bioethanol supply chains. Computers & Industrial Engineering, 2015. 87: p. 40-65.
18. Kostin, A., et al., Design and planning of infrastructures for bioethanol and sugar production under demand uncertainty. chemical engineering research and design, 2012. 90(3): p. 359-376.
19. Zhang, J., et al., An integrated optimization model for switchgrass-based bioethanol supply chain. Applied Energy, 2013. 102: p. 1205-1217.
20. Ahn, Y.-C., et al., Strategic planning design of microalgae biomass-to-biodiesel supply chain network: multi-period deterministic model. Applied Energy, 2015. 154: p. 528-542.
21. Dal-Mas, M., et al., Strategic design and investment capacity planning of the ethanol supply chain under price uncertainty. Biomass and bioenergy, 2011. 35(5): p. 2059-2071.
22. Chen, C.-W. and Y. Fan, Bioethanol supply chain system planning under supply and demand uncertainties. Transportation Research Part E: Logistics and Transportation Review, 2012. 48(1): p. 150-164.
23. Ghaderia, H., M. Asadia, and S. Shavvalpour, A Switchgrass-based Bioethanol Supply Chain Network Design Model under Auto-Regressive Moving Average Demand.
24. Akgul, O., et al., Optimization-based approaches for bioethanol supply chains. Industrial & Engineering Chemistry Research, 2010. 50(9): p. 4927-4938.
25. Bai, Y., et al., Biofuel refinery location and supply chain planning under traffic congestion. Transportation Research Part B: Methodological, 2011. 45(1): p. 162-175.
26. Ehrgott, M. and X. Gandibleux, Multiobjective combinatorial optimization—theory, methodology, and applications, in Multiple criteria optimization: State of the art annotated bibliographic surveys. 2003, Springer. p. 369-444.
27. Bérubé, J.-F., M. Gendreau, and J.-Y. Potvin, An exact ϵ-constraint method for bi-objective combinatorial optimization problems: Application to the Traveling Salesman Problem with Profits. European Journal of Operational Research, 2009. 194(1): p. 39-50.
28. Mele, F.D., et al., Multiobjective model for more sustainable fuel supply chains. A case study of the sugar cane industry in Argentina. Industrial & Engineering Chemistry Research, 2011. 50(9): p. 4939-4958.