پیوندهای مفید
آمار
| تعداد نشریات | 21 |
| تعداد شماره‌ها | 664 |
| تعداد مقالات | 9,698 |
| تعداد مشاهده مقاله | 69,032,518 |
| تعداد دریافت فایل اصل مقاله | 48,498,078 |
یک مدل چند هدفه استوار برای طراحی زنجیره تأمین با درنظرگیری جریان رو به جلو وعقب و مسئولیت‌پذیری اجتماعی | ||
| مدل سازی در مهندسی | ||
| مقاله 16، دوره 14، شماره 47، دی 1395، صفحه 171-185 اصل مقاله (1.97 M) | ||
| نوع مقاله: پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22075/jme.2017.2477 | ||
| نویسندگان | ||
| احمد ماکوئی* ؛ حمید صفاری؛ میر سامان پیشوایی؛ وحید محمودیان | ||
| دانشگاه علم و صنعت ایران | ||
| تاریخ دریافت: 18 تیر 1393، تاریخ بازنگری: 20 اسفند 1393، تاریخ پذیرش: 23 اردیبهشت 1394 | ||
| چکیده | ||
| در این مقاله مدلی چند هدفه ارائه شده است که در آن همزمان جریان رو به جلو و عقب در زنجیره تأمین در نظر گرفته شده و اهداف شامل هزینه و تأثیرات محیطی مانند میزان کربن دی اکسید و میزان مصرف آب و همچنین تأثیرات اجتماعی مانند میزان مشاغل ایجاد شده و عدالت در ایجاد مشاغل در نقاط مختلف می‌باشد. به علاوه در این تحقیق میزان تقاضا به صورت غیر قطعی بوده و با استفاده از روش برنامه‌ریزی استوار این عدم قطعیت وارد مدل‌سازی شده است. همچنین در مدل مورد نظر علاوه بر تعیین مکان بهینه تسهیلات و جریان بین آنها انتخاب نوع تکنولوژی و ظرفیت برای هر کارخانه تولیدی انجام میگیرد. در نهایت از صنعت فولاد برای پیاده‌سازی مدل ارائه شده استفاده شده است و نتایج نشان دهنده کارایی مدل استوار نسبت به مدل قطعی می‌باشد. | ||
| کلیدواژه‌ها | ||
| زنجیره تأمین حلقه بسته؛ لجستیک معکوس؛ مسئولیت پذیری اجتماعی؛ برنامه‌ریزی استوار | ||
| عنوان مقاله [English] | ||
| A robust multi objective model for forward â reverse supply chain designing based on social responsibility | ||
| نویسندگان [English] | ||
| Ahmad Makui؛ Hamid Saffari؛ Mir Saman Pishvaei؛ Vahid Mahmoodian | ||
| چکیده [English] | ||
| In this research, a multi-objective mix integer programming for supply chain is proposed in which forward and reverse logistic is considered, simultaneously. In addition to cost, minimization of the environmental influences such as carbon dioxide emission and water consumption and also the social issues such as generated jobs and their equitable distributionis considered. Moreover, it is assumed that the demand is uncertain and the problem has been modeled using robust optimization. Proposed model determines the type of technology and capacity of facilities other than optimal location and flows between them. Eventually, the efficiency of robust model is investigated by applying it on steel industry as a case study. | ||
| کلیدواژه‌ها [English] | ||
| Closed Loop Supply Chain, Reverse Logistics, Social responsibility, Robust Programming | ||
| مراجع | ||
|
ISO/TMB/WG/SR. )2006(.“Participating in the Future International Standard ISO 26000 on Social Responsibility”. International Organization for Standardization, Geneva.
[2] نیک نژاد، د.، (1388)، بررسی پیامدهای ناشی از گازهای گلخانه‌ای و اثرات آن برروی کره زمین، سومین کنفرانس محیط زیست، تهران.
[3] Fleischmann, M., Beullens, P., Bloemhof-Ruwaard, J.M., Van Wassenhove L.N. (2001). “Supply-chain network configuration for product recovery”. Production Planning & Control, 15, 270-281.
[4] Beamon, B.M., & Fernandes, C. (2004). “Supply-chain network configuration for product recovery”. Production Planning & Control, vol. 15, pp. 270-281..
[5] KO, H.J., Evans, G.W. (2007). “A genetic algorithm-based heuristic for the dynamic integrated forward/reverse logistics network for 3PLs”. Computers & Operations Research, vol. 34, pp. 346-366.
[6] Salema, M.I.G., Barbosa-Povoa, A.P., Novais, A.Q. (2007). “An optimization model for the design of a capacitated multi-product reverse logistics network with uncertainty”. European Journal of Operational Research, vol. 179, pp. 1063-1077.
[7] Pishvaee, M.S., Jolai, F., Razmi, J. (2009). “A stochastic optimization model for integrated forward/reverse logistics network design”. Journal of Manufacturing Systems, vol. 28, pp. 107-114.
[8] El-Sayed, M., Afia, N., El-Kharbotly, A. (2010). “A stochastic model for forward–reverse logistics network design under risk”. Computers & Industrial Engineering, vol. 58, pp. 423-431.
[9] Pishvaee, M.S., Torabi, S.A. (2010). “A possibilistic programming approach for closed-loop supply chain network design under uncertainty”. Fuzzy Sets and Systems, vol. 161, pp. 2668-2683.
[10] Pishvaee, M.S., Rabbani M., Torabi, S.A. (2011). “A robust optimization approach to closed-loop supply chain network design under uncertainty”. Applied Mathematical Modelling, vol. 35, pp. 637-649.
[11] Vahdani, B., Tavakkoli-Moghaddam, R., Modarres, M., Baboli, A. (2012). “Reliable design of a forward/reverse logistics network under uncertainty: A robust-M/M/c queuing model," Transportation Research Part E: Logistics and Transportation Review, vol. 48, pp. 1152-1168.
[12] Hasani, A., Zegordi, S.H., Nikbakhsh, E. (2012). “Robust closed-loop supply chain network design for perishable goods in agile manufacturing under uncertainty”. International Journal of Production Research, vol. 50, pp. 4649-4669.
[13] Ramezani, M., Bashiri, M., Tavakkoli-Moghaddam, R. (2013). “A new multi-objective stochastic model for a forward/reverse logistic network design with responsiveness and quality level”. Applied Mathematical Modelling, vol. 37, pp. 328-344.
[14] Faccio, M., Persona, A., Sgarbossa, F., Zanin, G. (2013). “Sustainable SC through the complete reprocessing of end-of-life products by manufacturers: A traditional versus social responsibility company perspective”. European Journal of Operational Research.
[15] Amin, S.H., & Zhang, G. (2012). “A multi-objective facility location model for closed-loop supply chain under uncertain demand and return”. Applied Mathematical Modeling, vol. 37, pp. 4165- 4176.
[16] Pishvaee, M.S., Razmi, J. (2012). “Environmental supply chain network design using multi-objective fuzzy mathematical programming”. Applied Mathematical Modelling, vol. 36, pp. 3433-3446.
[17] Wang, Y., Zhu, X., Lu, T., Jeeva, A.S. (2013) “Eco-efficient based logistics network design in hybrid manufacturing/ remanufacturing system in low-carbon economy”. Journal of Industrial Engineering and Management, vol. 6, pp. 200-214.
[18] Carter, C.R., Jennings, M.M. (2002). “Social responsibility and supply chain relationships”. Transportation Research Part E: Logistics and Transportation Review, vol. 38, pp. 37-52.
[19] Cruz, J.M., & Wakolbinger, T. (2008). “Multiperiod effects of corporate social responsibility on supply chain networks, transaction costs, emissions, and risk," International Journal of Production Economics, vol. 116, pp. 61-74.
[20] Cruz, J.M. (2009). “The impact of corporate social responsibility in supply chain management: Multicriteria decision-making approach”. Decision Support Systems, vol. 48, pp. 224-236.
[21] Dehghanian F., Mansour, S. (2009). “Designing sustainable recovery network of end-of-life products using genetic algorithm”. Resources, Conservation and Recycling, vol. 53, pp. 559-570.
[22] Pishvaee, M.S., Razmi, J., Torabi,, S.A. (2012). “Robust possibilistic programming for socially responsible supply chain network design: A new approach”. Fuzzy Sets and Systems, vol. 206, pp. 1-20.
[23] Mulvey, J.M. Vanderbei, R.J., Zenios, S.A. (1995). “Robust optimization of large-scale systems. Operations Research”. Operations Research,vol 43,pp.264-281.
[24] Yu, C.S., Li, H.L. (2000). “A robust optimization model for stochastic logistic problems”. International Journal of Production Economics, vol. 64, pp. 385-397.
[25] Torabi, S.A., Hassini, E. (2008). “An interactive possibilistic programming approach for multiple objective supply chain master planning”. Fuzzy Sets and Systems, vol. 159, pp. 193-214.
[26] Strezov, V., Evans, A., Evans, T. (2013) “Defining sustainability indicators of iron and steel production” .
Journal of Cleaner Production, vol. 51, pp. 66-70.
| ||
|
آمار تعداد مشاهده مقاله: 1,437 تعداد دریافت فایل اصل مقاله: 1,232 |
||