Optimal PET Recycling Management; Applying the Conditional Value-at-Risk (CVaR) Approach under Uncertainty for a Real Case

Document Type : Research Paper

Authors

1 Department of Energy Economics & Resources, Faculty of Economics, Kharazmi University, Tehran, Iran

2 Department of Economics, Faculty of Social Sciences and Economics, Alzahra University, Tehran, Iran

Abstract

In the pursuit of sustainable development goals, recycling has attracted a high level of attention around the world due to its economic and environmental benefits; however, applying the Conditional Value-at-Risk (CVaR) as an effective risk management approach for optimal Design of reverse supply chain (RSC) has been addressed by a few studies. This study mainly aims to achieve an optimal design for the RSC of recycling of polyethylene terephthalate (PET) bottles due to uncertainties in the market price of recycling materials, logistics costs, and the supply of raw materials. Considering the stochastic nature of the waste RSC parameters, two-stage stochastic programming models are developed in which the CVaR(Shortage) is utilized as a risk criterion to control shortages in demand centers. Moreover, the expected value of profit (E(Profit)) and the CVaR(Profit) are considered as two different objective functions. To evaluate efficiency and applicability, our selected models are implemented with the real data of Tehran’s Municipal Waste data. Comparing the empirical results indicate that using the CVaR(shortage) is an appropriate and reasonable approach to tackle the risk of a shortage in demand centers, and can be used to design the supply chain of other case studies. Also, the CVaR(Profit)) is more conservative in the face of the risk of shortage due to the risk-taking feature embedded in the objective function, which can be adjusted in accordance with the decision maker’s preference. The results additionally indicate that transportation cost plays an essential role in the cost structure of PET recycling stages.

Keywords

References

Alizadeh, M., Ma, J., Marufuzzaman, M., Yu, F., (2019). Sustainable olefin supply chain network design under seasonal feedstock supplies and uncertain carbon tax rate. Journal of Cleaner Production, Vol. 222, pp. 280-299.
Asefi, H., Shahparvari, S., Chhetri, P., (2019). Integrated Municipal Solid Waste Management under uncertainty: A tri-echelon city logistics and transportation context. Sustainable Cities and Society, Vol. 50, pp. 1-44. 101606.
Ayvaz, B., Bolat, B., Aydın, N., (2015). Stochastic reverse logistics network design for waste of electrical and electronic equipment. Resources, conservation and recycling, Vol. 104, pp.391-404.
Babazadeh, R., Sabbaghnia, A., (2018). Optimisation of supply chain networks under uncertainty: conditional value at risk approach. International Journal of Management and Decision Making, Vol. 17, pp. 488-508.
Babazadeh, R., TAVAKKOLI, M.R., Razmi, J., (2012). A complex design of the integrated forward-reverse logistics network under uncertainty, Vol. 12, pp. 113-123.
Bairamzadeh, S., Saidi-Mehrabad, M., Pishvaee, M.S., (2018). Modelling different types of uncertainty in biofuel supply network design and planning: A robust optimization approach. Renewable energy, Vol. 116, pp. 500-517.
Bing, X., Bloemhof-Ruwaard, J., Chaabane, A., van der Vorst, J., (2015). Global reverse supply chain redesign for household plastic waste under the emission trading scheme. Journal of cleaner production, Vol. 103, pp. 28-39.
Bing, X., Bloemhof-Ruwaard, J.M., van der Vorst, J.G., (2014). Sustainable reverse logistics network design for household plastic waste. Flexible Services and Manufacturing Journal, Vol. 26, pp. 119-142.
Bing, X., Bloemhof, J.M., Ramos, T.R.P., Barbosa-Povoa, A.P., Wong, C.Y., van der Vorst, J.G., (2016). Research challenges in municipal solid waste logistics management. Waste management, Vol. 48, pp. 584-592.
Chen, Y.-C., 2018. Effects of urbanization on municipal solid waste composition. Waste management, Vol. 79, pp. 828-836.
Chiadamrong, N., Piyathanavong, V., (2017). Optimal design of supply chain network under uncertainty environment using hybrid analytical and simulation modeling approach. Journal of Industrial Engineering International, Vol. 13, pp. 465-478.
Das, S., Lee, S.-H., Kumar, P., Kim, K.-H., Lee, S.S., Bhattacharya, S.S., (2019). Solid waste management: Scope and the challenge of sustainability. Journal of Cleaner Production. Vol. 228, pp. 658-678.
Dat, L.Q., Linh, D.T.T., Chou, S.-Y., Vincent, F.Y., (2012). Optimizing reverse logistic costs for recycling end-of-life electrical and electronic products. Expert Systems with Applications, Vol. 39, pp. 6380-6387.
Di Bernardino, E., Fernández-Ponce, J., Palacios-Rodríguez, F., Rodríguez-Griñolo, M., (2015). On multivariate extensions of the conditional Value-at-Risk measure. Insurance: Mathematics and Economics, Vol. 61, pp 1-16.
Diabat, A., Jebali, A., 2021. Multi-product and multi-period closed loop supply chain network design under take-back legislation. International Journal of Production Economics, Vol. 231, pp. 27-39. 107879.
Diaz-Barriga-Fernandez, A.D., Santibañez-Aguilar, J.E., Nápoles-Rivera, F., Ponce-Ortega, J.M., (2018). Analysis of the financial risk under uncertainty in the municipal solid waste management involving multiple stakeholders. Computers & Chemical Engineering, Vol. 117, pp. 433-450.
Ene, S., Öztürk, N., (2015). Network modeling for reverse flows of end-of-life vehicles. Waste management, Vol. 38, pp. 284-296.
Esmaeilizadeh, S., Shaghaghi, A., Taghipour, H., (2020). Key informants’ perspectives on the challenges of municipal solid waste management in Iran: a mixed method study. Journal of Material Cycles and Waste Management, Vol. 22, pp. 1-15.
Fan, K., Li, X., Wang, L., Wang, M., (2019). Two-stage supply chain contract coordination of solid biomass fuel involving multiple suppliers. Computers & Industrial Engineering, Vol.135, pp. 1167-1174.
Fazli-Khalaf, M., Chaharsooghi, S.K., Pishvaee, M.S., (2019). A new robust possibilistic programming model for reliable supply chain network design: A case study of lead-acid battery supply chain. RAIRO-Operations Research, Vol. 53, pp. 1489-1512.
Fazli-Khalaf, M., Hamidieh, A., (2017). A robust reliable forward-reverse supply chain network design model under parameter and disruption uncertainties. International Journal of Engineering-Transactions B: Applications, Vol. 30, pp. 1160-1169.
Ferronato, N., Gorritty Portillo, M.A., Guisbert Lizarazu, E.G., Torretta, V., Bezzi, M., Ragazzi, M., (2018). The municipal solid waste management of La Paz (Bolivia): Challenges and opportunities for a sustainable development. Waste Management & Research, Vol. 36, pp. 288-299.
Fleischmann, M., Bloemhof-Ruwaard, J.M., Dekker, R., Van der Laan, E., Van Nunen, J.A., Van Wassenhove, L.N., (1997). Quantitative models for reverse logistics: A review. European journal of operational research, Vol. 103, pp. 1-17.
Forouzanfar, F., Tavakkoli-Moghaddam, R., Bashiri, M., Baboli, A., Molana, S.H., (2018). New mathematical modeling for a location–routing–inventory problem in a multi-period closed-loop supply chain in a car industry. Journal of Industrial Engineering International, Vol. 14, pp. 537-553.
Gambella, C., Maggioni, F., Vigo, D., (2019). A stochastic programming model for a tactical solid waste management problem. European Journal of Operational Research, Vol. 273, pp. 684-694.
Garibay-Rodriguez, J., Laguna-Martinez, M.G., Rico-Ramirez, V., Botello-Alvarez, J.E., (2018). Optimal municipal solid waste energy recovery and management: a mathematical programming approach. Computers & Chemical Engineering Vol. 119, pp. 394-405.
Golroudbary, S.R., Zahraee, S.M., (2015). System dynamics model for optimizing the recycling and collection of waste material in a closed-loop supply chain. Simulation Modelling Practice and Theory, Vol. 53, pp. 88-102.
Govindan, K., Soleimani, H., Kannan, D., (2015). Reverse logistics and closed-loop supply chain: A comprehensive review to explore the future. European Journal of Operational Research, Vol. 240, pp. 603-626.
Gumte, K., Pantula, P.D., Miriyala, S.S., Mitra, K., (2021). Achieving Wealth from Bio-Waste in a Nationwide Supply Chain Setup under Uncertain Environment through Data Driven Robust Optimization Approach. Journal of Cleaner Production, Vol.291, pp.167-176. 125702
Habibi, F., Asadi, E., Sadjadi, S.J., Barzinpour, F., (2017). A multi-objective robust optimization model for site-selection and capacity allocation of municipal solid waste facilities: A case study in Tehran. Journal of cleaner production, Vol. 166, pp. 816-834.
Hamidieh, A., Fazli-Khalaf, M., (2017). A possibilistic reliable and responsive closed loop supply chain network design model under uncertainty. Journal of Advanced Manufacturing Systems, Vol. 16, pp. 317-338.
Han, X., Hu, C., Lin, L., (2019). A study on the impact of China’s urbanization on the quantity of municipal solid waste produced. Waste Management & Research, Vol.38, pp.184-192. 0734242X19886912.
Heidari, R., Yazdanparast, R., Jabbarzadeh, A., (2019). Sustainable design of a municipal solid waste management system considering waste separators: A real-world application. Sustainable Cities and Society, Vol. 47, pp. 92-101. 101457.
Hu, B., Feng, Y., (2017). Optimization and coordination of supply chain with revenue sharing contracts and service requirement under supply and demand uncertainty. International Journal of Production Economics, Vol. 183, pp. 185-193.
IPRC, (2018). Islamic Parliament Research Center Of The Islamic Republic Of IRAN, in: Researches, D.o.I.a.P. (Ed.), Iran.
Kara, S.S., Onut, S., (2010). A two-stage stochastic and robust programming approach to strategic planning of a reverse supply network: The case of paper recycling. Expert Systems with Applications, Vol. 37, pp. 6129-6137.
Kazemzadeh, N., Hu, G., (2013). Optimization models for biorefinery supply chain network design under uncertainty. Journal of Renewable and Sustainable Energy, Vol. 5, pp. 41-53..053125.
Kheyrollahi, M., nadi , s., Neisany Samany , N., (2016). Conflating qualitative and quantitative criteria using location-based models for optimal routing of emergency vehicles in urban environments. Scientific-Research Quarterly of Geographicl Data (SEPEHR) Vol. 25, pp. 45-59.
Kleinow, J., Moreira, F., Strobl, S., Vähämaa, S., (2017). Measuring systemic risk: A comparison of alternative market-based approaches. Finance Research Letters Vol. 21, pp. 40-46.
Klibi, W., Martel, A., Guitouni, A., (2010). The design of robust value-creating supply chain networks: a critical review. European Journal of Operational Research Vol. 203, pp. 283-293.
Komly, C.-E., Azzaro-Pantel, C., Hubert, A., Pibouleau, L., Archambault, V., (2012). Multiobjective waste management optimization strategy coupling life cycle assessment and genetic algorithms: Application to PET bottles. Resources, conservation and recycling Vol. 69, pp. 66-81.
Liu, Z., Nagurney, A., (2013). Supply chain networks with global outsourcing and quick-response production under demand and cost uncertainty. Annals of Operations Research Vol. 208, pp. 251-289.
Mahnam, M., Yadollahpour, M.R., Famil-Dardashti, V., Hejazi, S.R., (2009). Supply chain modeling in uncertain environment with bi-objective approach. Computers & Industrial Engineering Vol. 56, pp. 1535-1544.
Mohsenizadeh, M., Tural, M.K., Kentel, E., (2020). Municipal solid waste management with cost minimization and emission control objectives: A case study of Ankara. Sustainable Cities and Society Vol. 52, pp. 172-187.101807.
Mwanza, B.G., Mbohwa, C., (2017). Drivers to sustainable plastic solid waste recycling: a review. Procedia Manufacturing, Vol. 8, pp. 649-656.
Nagurney, A., Toyasaki, F., (2005). Reverse supply chain management and electronic waste recycling: a multitiered network equilibrium framework for e-cycling. Transportation Research Part E: Logistics and Transportation Review, Vol. 41, pp. 1-28.
Nayeri, S., Paydar, M.M., Asadi-Gangraj, E., Emami, S., (2020). Multi-objective fuzzy robust optimization approach to sustainable closed-loop supply chain network design. Computers & Industrial Engineering, Vol. 148, pp. 109-121.106716.
Paydar, M.M., Olfati, M., (2018). Designing and solving a reverse logistics network for polyethylene terephthalate bottles. Journal of cleaner production, Vol. 195, pp. 605-617.
Pflug, G.C., (2000). Some remarks on the value-at-risk and the conditional value-at-risk, Probabilistic constrained optimization. Springer, pp. 272-281.
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.
Preston, F., Lehne, J., Wellesley, L., (2019). An Inclusive Circular Economy: Priorities for Developing Countries. London: The Royal Institute of International Affairs. pp. 1-139.
Rai, B., Goswami, S., (2019). Urbanization and Tourism Induced Challenges in Waste Management in Hill Towns: Case of Gangtok, Waste Management and Resource Efficiency. Springer, pp. 393-407.
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.
Rockafellar, R.T., Uryasev, S., (2000). Optimization of conditional value-at-risk. Journal of risk, Vol. 2, pp. 21-42.
Rodić, L., Wilson, D.C., (2017). Resolving governance issues to achieve priority sustainable development goals related to solid waste management in developing countries. Sustainability, Vol. 9, pp. 404-418.
Sanjeevi, V., Shahabudeen, P., (2015). Development of performance indicators for municipal solid waste management (PIMS): A review. Waste Management & Research, Vol.  33, pp. 1052-1065.
Senthil, S., Murugananthan, K., Ramesh, A., (2018). Analysis and prioritisation of risks in a reverse logistics network using hybrid multi-criteria decision making methods. Journal of cleaner production, Vol. 179, pp. 716-730.
Shih, L.-H., (2001). Reverse logistics system planning for recycling electrical appliances and computers in Taiwan. Resources, conservation and recycling, Vol. 32, pp. 55-72.
Singh, A., (2019). Managing the uncertainty problems of municipal solid waste disposal. Journal of environmental management, Vol. 240, pp. 259-265.
TURPC, (2018). Tehran Urban Research & Planning Center, Iran- Tehran.
Uryasev, S., (2013). Probabilistic constrained optimization: methodology and applications. Springer Science & Business Media.
Wang, H., Nie, Y., (2001). Municipal solid waste characteristics and management in China. Journal of the Air & Waste Management Association, Vol. 51, pp. 250-263.
WDI, (2019). World Bank, Urban poulation growth.
Wilcox, W., Horvath, P.A., Griffis, S.E., Autry, C.W., (2011). A Markov model of liquidity effects in reverse logistics processes: The effects of random volume and passage. International Journal of Production Economics, Vol. 129, pp. 86-101.
Xu, Z., Elomri, A., Pokharel, S., Zhang, Q., Ming, X., Liu, W., (2017). Global reverse supply chain design for solid waste recycling under uncertainties and carbon emission constraint. Waste management Vol. 64, pp. 358-370.
Zhou, X., Wang, C., Fang, C., Yu, R., Li, Y., Lei, W., (2019). Structure and thermal properties of various alcoholysis products from waste poly (ethylene terephthalate). Waste management, Vol.  85, pp. 164-174.
Zhu, S., Fukushima, M., (2009). Worst-case conditional value-at-risk with application to robust portfolio management. Operations research, Vol. 57, pp. 1155-1168.
International Journal of Supply and Operations Management
Volume 8, Issue 3
August 2021
Pages 264-288

Files

Share

How to cite

Statistics