Presenting a reverse logistics optimization model to reduce environmental effects based on waste management

Subject Areas :

Mahta Kakooee ¹ , Mahmoud Modiri ^{2 *} , Ghanbar Abbaspour Esfeden ³

1 - PhD student in Industrial Management, South Tehran Branch, Islamic Azad University, Tehran, Iran
2 - Department of Management industrial, South Tehran Branch, Islamic Azad University, Tehran, Iran.
3 - Department of Industrial Management, South Tehran Branch, Islamic Azad University, Tehran, Iran

Received: 2024-01-17 Accepted : 2024-06-13 Published : 2024-07-02

Keywords: Model, Optimization, Reverse Logistic, Waste Management, Environmental Impact,

Abstract :

Purpose: 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.

Research methodology: This research presents a model to reduce environmental impacts. This research includes an eleven-level, multi-product reverse logistics network that is capable of supporting a variety of industries whose products are at the end of their life cycle. This research designs a reverse logistics network that collects all waste in one place and separates it based on the needs of the factories (in terms of type and nature of waste, etc.) and sends it to the desired destination for recycling. In this research, a mixed mathematical model is presented to reduce the costs of the entire system. In this research, after solving the model, the model is validated with different data and sensitivity analysis is performed for the key parameters of the model.

Findings The number of facility centers, the number of products and parts to be shipped from one center to another, the amount of CO2 emissions, and the total cost of the model are specified. Finally, sensitivity analysis is performed on the model parameters and the model is validated by changing the input data in two different cases. Sensitivity analyses are performed on different parameters to demonstrate the capabilities of the proposed model. The results show that the allowable cost of CO2 emissions has a significant impact on the value of the objective function.

Originality/scientific added value: Today, population growth and rapid urbanization, along with rising social standards of living, have significantly accelerated the production of solid waste in the world. Solid waste has become one of the most important environmental issues worldwide.

References:

 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(