نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشگاه آزاد اسلامی واحد تهران شمال

2 مهندسی صنایع، دانشکده فنی و مهندسی، دانشگاه آزاد اسلامی واحد تهران شمال

چکیده

افزایش توجه به مسائل زیست محیطی اهمیت مسئله طراحی زنجیره‌های تأمین حلقه بسته را که شامل تولید و بازیافت و امحاء ضایعات است، دو چندان کرده است. مسئله طراحی یکپارچه شبکه‌های زنجیره تأمین حلقه بسته به عنوان یکی از مسائل مهم در مدیریت زنجیره‌های تأمین شامل تعیین هم‌زمان مکان و تعداد تسهیلات مورد نیاز (تولید، جمع‌آوری، بازیافت و انهدام) در زنجیره تأمین رو به جلو و معکوس، موجودی هر تسهیل و کمیت جریان ارسالی بین آن‌ها می‌باشد. در این مقاله، زنجیره تأمین حلقه بسته‌ای با محصولات متنوع (چند محصولی) مطالعه شده و یک مدل برنامه‌ریزی ‌ریاضی خطی دو هدفه (کاهش هزینه‌های کل زنجیره و میزان آلایندگی‌های زیست محیطی) به منظور تعیین متغیرهای راهبردی مسئله شامل مکان‌یابی مراکز تولید، جمع‌آوری و انهدام محصولات و متغیرهای عملیاتی در دوره‌های مختلف برنامه‌ریزی (چند دوره‌ای) شامل جریان‌های بین تسهیلات به تفکیک وسایل نقلیه مختلف و موجودی‌های هر تسهیل ارائه شده است. به دلیل وجود عدم قطعیت در پارمترهایی مانند تقاضا و میزان کالای برگشتی از مشتریان، مدل پیشنهادی در شرایط عدم قطعیت (بهینه‌سازی استوار) توسعه یافته است. ضمن بررسی اعتبارسنجی مدل، کاربرد مدل پیشنهادی برای طراحی شبکه تأمین و بازیافت بطری‌های شیشه‌ای با هدف کاهش هزینه‌های احداث مراکز و حمل و نقل‌ها برای محصولات مختلف و در کل دوره برنامه ریزی به اضافه کمینه‌کردن کل گاز دی اکسید کربن تولیدی بررسی شده است. تحلیل حساسیت مدل بهینه‌سازی استوار نیز در پایان انجام شده است.

کلیدواژه‌ها

عنوان مقاله [English]

A Bi-Objective Model to Design Closed-Loop Supply Chain Network under Uncertainty

نویسنده [English]

  • Zahra Safari 2

1

2 Industrial Engineering Department, Islamic Azad University, Tehran North Branch, Tehran, Iran.

چکیده [English]

By increasing attention to environmental issues, the problem of design closed-loop supply chain has been more important. The integrated design of closed-loop supply chains as one of the most important issues in the management of supply chains involve determining the location and number of required facilities (production, collection, recycling and disposal) in the forward and reverse supply chain, inventories in every facility and flows between them. In this paper, a closed-loop supply chain with diverse products (multi-product) has been studied and a linear bi-objective mathematical model is proposed to reduce the total costs and the emissions in the network with determining the strategic and operational variables. Because of the uncertainty in parameters of proposed model such as customer demands or returns, the proposed model under uncertainty (robust optimization) is developed. The closed-loop supply chain of glass bottles is studied and modeled to minimize the total costs and production of carbon dioxide by proposed model. Finally, a sensitivity analysis of robust optimization model was conducted.

کلیدواژه‌ها [English]

  • Supply chain network design
  • closed-loop supply chain
  • Robust Optimization
  • Green supply chain
اصغرپور، محمد جواد (1388)، تصمیم‌گیری‌های چندمعیاره، چاپ اول، انتشارات دانشگاه تهران، تهران، ایران.
عامری، محمود، زاهد، فاطمه (1392)، «براورد هزینه خارجی گرمایش جهانی ناشی از بهره برداری آزادراه های کشور»، محیط شناسی، سال سی و نهم، شماره 3، ص 212-201.
عمرانی، قاسم علی،  منوری، سید مسعود، جوزی، سید علی، زمانی، ندا (1388)، «مدیریت بازیافت شیشه در شهر تهران»، علوم و تکنولوژی محیط زیست، دوره یازدهم، شماره 4، ص. 50-41.
یحیی‌زاده اندواری، یلدا، الفت، لعیا و امیری، مقصود (1395)، «رویکرد بهینه‌سازی استوار در انتخاب تأمین کننده و تخصیص سفارش»، مطالعات مدیریت صنعتی، سال چهاردهم، شماره 40، ص 52-25.
Amaro, A. and Barbosa-Póvoa, A.P.F (2009), “The effect of uncertainty on the optimal closed-loop supply chain planning under different partnerships structure”, Computers & Chemical Engineering, Vol. 33, No. 12, PP: 2144-2158.
Amin, S. H. and Baki, F (2017), “A facility location model for global closed-loop supply chain network design”, Applied Mathematical Modelling, Vol. 41, PP: 316-330. 
Amin, S.H. and Zhang, G (2013), “A multi-objective facility location model for closed-loop supply chain network under uncertain demand and return”, Applied Mathematical Modelling, Vol. 37, No.6, PP: 4165-4176.
Amin, S.H., Zhang, G. and Akhtar, P (2017), “Effects of Uncertainty on a Tire Closed-loop Supply Chain Network”, Expert Systems with Applications, Vol. 73, No. 1, PP: 81-91.
Baghalian, A., Rezapour, S. and Farahani, R.Z. (2013), “Robust supply chain networkdesign with service level against disruptions and demand uncertainties: A real-life case”, European Journal of Operational Research, Vol. 227, No.1, PP: 199-215.
Bekmann M. and Kunzi  H. P (1996), Lecture Notes in Economics and Mathematical Systems Theories and Applications, Springer, (Multi-Objective Programming and Goal Programming).
Cardoso, S.R., Barbsosa-Plvoa, A.P. and Revas, S (2016), “Integrating financial risk measures into the design and planning of closed-loop supply chains”, Computers & Chemical Engineering, Vol. 85, PP: 105-123.
Dutta, P., Das, D., Schultmann, F. and Frohling, M (2016), “Design and planning of a closed-loop supply chain with three way recovery and buy-back offer”, Journal of Cleaner Production, Vol. 135, PP: 604-619.
Fallah, H., Eskandari, H. and Pishvaee, M.S (2015), “Competitive closed-loop supply chain network design under uncertainty”, Journal of Manufacturing Systems, Vol. 37, No. 3, PP:649-661.
Farrokh, M., Azar, A., Janaghi, G. and Ahmadi, E (2017), “A novel robust fuzzy stochastic programming for closed loop supply chain network design under hybrid uncertainty”, Fuzzy Sets and Systems, In Press.
Fleischmann, M., Beullens, P., Bloemhof-Ruwaard, J.M. andWassenhove, L.N. (2001), “The impact of product recovery on logistics network design”, Production and Operations Management, Vol. 10, No.2, PP:156-173.
Gaur, J., Amini, M. and Rao, A. K (2017). “Closed-loop supply chain configuration for new and recinditioned products”, An integrated optimiization model, Omega, Vol. 66, Part B, PP: 212-223.
Govindan, K. and Soleimani, H (2017), “A review of reverse logistics and closed-loop supply chains: a Journal of Cleaner Production focus”, Journal of Cleaner Production, Vol. 142, Part 1, PP: 371-384. 
Govindan, K., Soleimani, H. and Kannan, D (2015), “Reverse logistics and closed-loop supply chain: A comprehensive review to explore the future”, European Journal of Operational Research, Vol. 240, No. 3, PP: 603-626.
Keyvanshokooh, E., Ryan, S.M. and Kabir, E (2016), “Hybrid robust and stochastic optimization for closed loop supply chain network design using accelerated Benders decomposition”, European Journal of Operartional Resaeach, Vol. 249, No. 1, PP: 76-92.
Ko, H.J. and Evans G.W (2007), “A genetic algorithm-based heuristic for the dynamic integrated forward/reverse logistics network for 3PLs”, Computers & Operations Research, Vol. 34, No. 2, PP: 346-366.
Lee, D.H. and Dong M (2009), “Dynamic network design for reverse logistics operations under uncertainty”, Transportation Research PartE: Logistics and Transportation Review, Vol. 45, No. 1, PP: 61-71.
Lee, D.H. and Dong, M (2008), “A heuristic approach to logistics network design for end-of-leasecomputer products recovery”, Transportation Research Part E: Logistics and Transportation Review, Vol. 44, No. 3, PP: 455-474.
Leung, S., Tsang, S., Ng, W.L. and Wu, Y (2007), A robust optimization model for multi-site production planning problem in an uncertain environment”, European Journal of Operational Research, Vol. 181, PP: 224–238.
Lu, Z. and Bostel N (2007), “A facility location model for logistics systems including reverse flows: The case of remanufacturing activities”, Computers & Operations Research, Vol. 34, No.2, PP: 299-323.
Ma, R., Yao, L., Jin, M., Ren, P. and Lv, Z (2016), “Robust environmental closed-loop supply chain design under uncertainty”, Chaos, Solitons and Fractals, Vol. 89, PP: 195-202. 
Melo, M.T., Nickel, S., and Saldanha-da-Gama, F (2009), "Facility location and supply chain management–A review", European Journal of Operational Research, Vol.196, No.2, PP: 401-412.
Meysam, S.K., Maghsud, S., Ali, D (2016) “An integrated supply chain configuration model and procurement management under uncertainty: a set-based robust optimization methodology”, Applied Mathematical Modelling, Vol. 40, No. 117-18, PP: 7928-7947.
Min, H. and Ko, H.-J (2008), “The dynamic design of a reverse logistics network from the perspective of third-party logistics service providers”, International Journal of Production Economics, Vol. 113, No.1, PP: 176-192.
Mohajeri, A. and Fallah, M (2016), “A carbon footprint-based closed-loop supply chain model under uncertainty with risk analysis: A case study”, Transportation Research Part D, Vol. 48, PP: 425-450.
Mohammed, F., Selim, S. Z., Hassan, A. and Syed, M.N (2017),” Multi-period planning of closed-loop supply chain with carbon policies under uncertainty”, Transportation Research Part D, Vol. 51, PP: 146-172.
Moshtagh, M.S. and Taleizadeh, A.A (2017), “Stochastic integrated manufacturing and remanufacturing model with shortage, rework and quality based return rate in a closed loop supply chain”, Journal of Cleaner Production, Vol. 141, PP: 1548-1573.
Mulvey, J.M., Vanderbei, R.J., and Zenios, S.A (2005), “Robust optimization of large-scale systems”, Operations research, Vol. 43, No. 2, PP: 264-281.
Özkır, V. and Başlıgil, H (2013), "Multi-objective optimization of closed-loop supply chains in uncertain environment", Journal of Cleaner Production, Vol. 41, PP: 114-125.
Pishvaee, M. and Torabi, S (2010), "A possibilistic programming approach for closed-loop supply chain network design under uncertainty', Fuzzy sets and systems, Vol. 161, No. 20, PP: 2668-2683.
Pishvaee, M.S., Farahani, R.Z. and Dullaert, W (2010a), "A memetic algorithm for bi-objective integrated forward/reverse logistics network design", Computers & Operations Research, Vol. 37, No. 6, PP: 1100-1112.
Pishvaee, M.S., Jolai, F., and Razmi, J (2009), "A stochastic optimization model for integrated forward/reverse logistics network design", Journal of Manufacturing Systems, Vol. 28, No.4, PP. 107-114.
Pishvaee, M.S., Rabbani, M., and Torabi S.A (2011), "A robust optimization approach to closed-loop supply chain network design under uncertainty", Applied Mathematical Modelling, Vol. 35, No. 2, PP: 637-649.
Ramezani, M., Bashiri, M. and Tavakkoli-Moghaddam, R (2013a), "A new multi-objective stochastic model for a forward/reverse logistic network design with responsiveness and quality level", Applied Mathematical Modelling, Vol. 37, No. 1, PP: 328-344.
Ramezani, M., Bashiri, M. and Tavakkoli-Moghaddam, R (2013b), "A robust design for a closed-loop supply chain network under an uncertain environment", The International Journal of Advanced Manufacturing Technology, Vol. 66, No. 5-8, PP: 825-843.
Ramezani, M., Kimiagari, A.M. and Karimi, B (2014a), "Closed-loop supply chain network design: A financial approach", Applied Mathematical Modelling, Vol. 38, No. 15-16, PP:4099-4119.
Ramezani, M., Kimiagari, A.M., Karimi, B. and Hejazi, T.H (2014b), "Closed-loop supply chain network design under a fuzzy environment", Knowledge-Based Systems, Vol. 59, PP: 108-120.
Rezapour, S., Farahani, R.Z., Fahimnia, B., Govindan, K. and Mansouri, Y. (2015), "Competitive closed-loop supply chain network design with price-dependent demands", Journal of Cleaner Production, Vol. 93, PP: 251-272.
Salema, M., Póvoa, A. and Novais A (2006), "A warehouse-based design model for reverse logistics", Journal of the Operational Research Society, Vol. 57, No.6, PP: 615-629.
Salema, M.I.G., Barbosa-Povoa, A.P. and 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, No. 3, PP: 1063-1077.
Sarkar, B., Ullah, M. and Kim, N (2017), “Environmental and economic assessment of closed-loop supply chain with remanufacturing and returnable transport items”, Computers and Industrial Engineering, Vol. 111, PP: 148-163.
Soleimani, H. and Kannan G (2015), "A hybrid particle swarm optimization and genetic algorithm for closed-loop supply chain network design in large-scale networks", Applied Mathematical Modelling, Vol. 39, No. 14, PP: 3990-4012.
Souza, G. C (2013), “Closed-Loop Supply Chains: A Critical Review, and Future Research”, Decision Sciences, Vol. 44, No. 1, PP: 7-38.
Subulan, K., Baykasoğlu, A., Özsoydan, F.B., Taşan, A.S. and Selim, H (2015), "A case-oriented approach to a lead/acid battery closed-loop supply chain network design under risk and uncertainty", Journal of Manufacturing Systems, Vol. 37, No.1, PP: 340-361.
Talaei, M., Moghaddam, B. F., Pishvaee, M. S., Bozorgi-Amiri, A. and Gholamnejad, S. (2016), “A robust fuzzy optimization model for carbon-efficient closed-loop supply chain network design problem: a numerical illustration in electronics industry”, Journal of Cleaner Production, Vol. 113, PP: 662-673.
Üster, H., Easwaran, G. Akçali, E. and Cetinkaya, S (2007), "Benders decomposition with alternative multiple cuts for a multi‐product closed‐loop supply chain network design model", Naval Research Logistics (NRL), Vol 54, No. 8, PP: 890-907.
Vahdani, B., Razmi, J. and Tavakkoli-Moghaddam, R(2012), "Fuzzy possibilistic modeling for closed looprecycling collection networks", Environmental Modeling & Assessment, Vol. 17, No. 6, PP:623-637.
Wang, H.-F. and Hsu H.-W (2010), "A closed-loop logistic model with a spanning-tree based genetic algorithm", Computers & Operations Research, Vol. 37, No. 2, PP: 376-389.
Yu, C.S and Li, H.L (2000), "A robust optimization model for stochastic logsistic problems", Internatioanl Journal of Production Economics, Vol. 64, PP: 385-397.
Zeballos, L.J., Méndez, C.A., Barbosa-Povoa, A.P. and Novais, A.Q (2014), "Multi-period design and planning of closed-loop supply chains with uncertain supply and demand", Computers & Chemical Engineering, Vol. 66, PP: 151-164.
Zhou, X. C., Zhao, Z. X., Zhou, K. J. and He, C.H (2012), "Remanufacturing closed-loop supply chain network design based on genetic particle swarm optimization algorithm", Journal of Central South University, Vol. 19, PP: 482-487.
Zohal, M. and Soleimani, H (2016), “Developing an ant colony approach for green closed-loop supply chain network design: a case study in gold industry”, Journal of Cleaner Production, Vol. 133, PP: 314-337.