Designing a Multi-Objective Stable Mathematical Model for Routing Municipal Waste Collection Vehicles

Document Type : Research Paper


1 PhD Candidate, Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.

2 Associate Prof., Department of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran.

3 Associate Prof., Department of Mathematics, Nour Branch, Islamic Azad University, Nour, Iran.

4 Assistant Prof., Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.


Waste collection poses a significant challenge for contemporary societies. Given the inevitability of ongoing human waste production, the organization of municipal waste collection holds paramount importance. Against the backdrop of escalating environmental pollutants over recent decades and crises induced by global warming, governments have increasingly prioritized addressing sustainability issues. The objective of this study was to formulate an urban waste collection network with a municipal sustainability perspective. To achieve this goal, we proposed a multi-objective mathematical model that incorporates economic, social, and environmental considerations pertaining to the routing of urban waste collection vehicles.
This study introduces an integer multi-objective mathematical model centred on stability components to address the routing problem of urban waste collection vehicles, to design an optimal network for urban waste collection. The model was addressed using real data from waste collection in Iran’s Saveh city. GAMS software was employed for solving the model in small dimensions, while MATLAB software was utilized for solving the model in larger dimensions. The proposed model incorporates a robust approach to handle uncertainty. Multi-objective meta-heuristic algorithms were applied to solve the model in scenarios with larger dimensions. A comparative analysis was subsequently conducted, evaluating solution methods based on both the values of the objective function and the solution time.
The economic objective of this study encompasses the overall costs associated with transporting waste from collection points to processing and recycling centres, along with the expenses related to waste recycling. Its environmental objective focuses on minimizing pollution resulting from the transportation of collected waste. Lastly, its social objective is to maximize citizens' satisfaction with urban waste collection. The results demonstrated that the proposed mathematical model establishes a rational relationship between the incurred costs, the quantity of waste collected, the distance travelled, and the amount of pollution generated during the transportation of waste.
The model presented in this study optimized the urban waste collection system by incorporating dimensions of sustainability. This was achieved by formulating separate objective functions to address various aspects of urban waste collection. The results showed that in the economic dimension, waste collection costs, which account for the largest share of the total cost of waste management, decreased significantly. The collection cost was reduced by optimizing the collection routes and reducing the costs related to recycling collected waste. In addition, in the social dimension, by considering the amount of waste collected compared to the waste produced, the level of satisfaction of citizens was calculated. Finally, the results showed that by reducing the environmental effects related to the recycling and transportation of the collected waste, the proposed model had an acceptable performance.


Main Subjects

Abdelli, I.S., Abdelmalek, F., Djelloul, A., Mesghouni, K., Addou, A. (2016). GIS based approach for optimized collection of household waste in Mostaganem city (Western Algeria). Waste Management & Research, 34 (5), 417–426.
Babaee Tirkolaee, E., Mahdavi, I., Seyyed Esfahani, M. M., (2018). A robust periodic capacitated arc routing problem for urban waste collection considering drivers and crew’s working time. Waste Management, 76, 138-146.
Boskovic, G., Jovicic, N., Jovanovic, S., Simovic, V. (2016). Calculating the costs of waste collection: a methodological proposal. Waste Manage. Res., 34 (8), 775–783.
Dai, C., Li, Y. P., Huang. G. H. (2011). A two-stage support-vector-regression optimization model for municipal solid waste management – A case study of Beijing, China, Journal of Environmental Management, 92(12), 3023-3037.
Edalatpour, M. A., Mirzapour Al-e-hashem, S. M. J., Karimi, B., Bahli, B. (2018). Investigation on a novel sustainable model for waste management in megacities: A case study in Tehran municipality. Sustainable Cities and Society, 36, 286-301.
Erkut, E., Karagiannidis, A., Perkoulidis, G., & Tjandra, S. A. (2008). A multicriteria facility location model for municipal solid waste management in North Greece. European Journal of Operational Research, 187, 1402–1421.
Eslampanah, A., Jafarnezhad, A., Heidary, J. & Taghizadeh-Yazdi, M. (2023). Utilizing Vehicular Ad Hoc Networks (VANET) for the Design of an Industrial Waste Reverse Supply Chain: A Case Study in the Iranian Automotive Industry. Industrial Management Journal, 15(3), 447-477. (in Persian)
Faccio, M., Persona, A., Zanin, G. (2011). Waste collection multi objective model with real time traceability data. Waste Management, 31 (12), 2391–2405.
Fernández-Aracil, P., Ortuño-Padilla, A., Melgarejo-Moreno. J. (2018). Factors related to municipal costs of waste collection service in Spain. Journal of Cleaner Production, 17520, 553-560.
Ferri, G. L., de Lorena Diniz Chaves, G., & Ribeiro, G. M. (2015). Reverse logistics network for municipal solid waste management: The inclusion of waste pickers as a Brazilian legal requirement. Waste Management, 40, 173–191.
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, 1192, 39405.
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, 166, 816–834.
Ibáñez-Forés, V., Coutinho-Nóbrega, C., Bovea, M. D., Mello-Silva, C. de Júlia Lessa-Feitosa-Virgolino. (2018). Influence of implementing selective collection on municipal waste management systems in developing countries: A Brazilian case study, Resources, Conservation and Recycling, 134, 100-111.
Inghels, D., Dullaert, W. & Vigo, D. (2016). A service network design model for multimodal municipal solid waste transport, European Journal of Operational Research, 254(1), 68-79.
Jaunich, M.K., Levis, J.W., DeCarolis, J.F., Gaston, E.V., Barlaz, M.A., Bartelt-Hunt, S.L., Jones, E.G., Hauser, L., Jaikumar, R. (2016). Characterization of municipal solid waste collection operations. Resour. Conserv. Recycl., 114, 92–102.
Li, Y., & Huang, G. (2010). An interval-based possibilistic programming method for waste management with cost minimization and environmental-impact abatement under uncertainty. Science of the total environment, 408(20), 4296-4308.
Mello, V. M., Santos, D., Freitas, R., Yokoyama, L. & Cammarota, M. C. (2018). Energy generation in the treatment of effluent from washing of municipal solid waste collection trucks. Sustainable Energy Technologies and Assessments, 30, 105-113.
Mirdar Harijani, A., Mansour, S., & Karimi, B. (2017b). Multi-period sustainable and integrated recycling network for municipal solid waste – A case study in Tehran. Journal of Cleaner Production, 151, 96–108.
Mohammaditabar, D., Ghodsypour, SH. & Hafezalkotob, A. (2015). A game theoretical analysis in capacity-constrained supplier-selection and cooperation by considering the total supply chain inventory costs. International Journal of Production Economics, 181, 87-97.
Nguyen, T.K., Nguyen, T.N.A., Nguyen, N.D., Dinh, T.H.V. (2017). Optimization of municipal solid waste transportation by integrating GIS analysis, equation based, and agent-based model. Waste Management, 59, 14–22. 10.1016/j.wasman.2016.10.048.
Phillips, J., Mondal. M. K. (2014). Determining the sustainability of options for municipal solid waste disposal in Varanasi, India. Sustainable Cities and Society, 10, 11-21.
Rahmanifar, G., Mohammadi, M., Sherafat, A., Hajiaghaei-Keshteli, M., Fusco, G., & Colombaroni, C. (2023). Heuristic approaches to address vehicle routing problem in the Iot-based waste management system. Expert Systems with Applications, 220, 119708.
Richter, A., Ng, K.T.W., Pan, C., 2018. Effects of Percent Operating Expenditure on Canadian Non-hazardous Waste Diversion. Sustainable Cities and Society, 38, 420–428.
Sanjeevi, V., Shahabudeen, P., 2016. Optimal routing for efficient municipal solid waste transportation by using ArcGIS application in Chennai. India. Waste Manage. Res. 34 (1), 11–21.
Santibañez-Aguilar, J. E., Ponce-Ortega, J. M., González-Campos, J. B., Serna-González, M., El-Halwagi. M. (2013). Optimal planning for the sustainable utilization of municipal solid waste, Waste Management, 33(12), 2607-2622.
Soltani, A., Sadiq, R., Hewage, K. (2017). The impacts of decision uncertainty on municipal solid waste management. Journal of Environmental Management, 19715, 305-315.
Son, L.H., Louati, A., 2016. Modeling municipal solid waste collection: a generalized vehicle routing model with multiple transfer stations, gather sites and inhomogeneous vehicles in time windows. Waste Manage., 52, 34–49.
Soukopová, J., Struk, M., Hřebíček. (2017). Population age structure and the cost of municipal waste collection. A case study from the Czech Republic, Journal of Environmental Management, 203, 655-663.
Tavares, G., Zsigraiova, Z., Semiao, V. & Carvalho M. G. (2009). Optimisation of municipal solid waste collection routes for minimum fuel consumption using 3D GIS modelling. Waste Management, 29(3), 1176-1185.
Tirkolaee, E. B., Goli, A., Gütmen, S., Weber, G. W., & Szwedzka, K. (2023). A novel model for sustainable waste collection arc routing problem: Pareto-based algorithms. Annals of Operations Research, 324(1-2), 189-214.
Valizadeh, J., Mozafari, P., & Hafezalkotob, A. (2022). Municipal waste management and electrical energy generation from solid waste: a mathematical programming approach. Journal of Modelling in Management, 17(1), 309-340.
Valizadeh, J., Sadeh, E., Amini, Z. & Hafezalkotob, A. (2020). Robust optimization model for sustainable supply chain for production and distribution of Polyethylene pipe, Journal of Modelling in Management, 15(4), 1613-1653.
Valizadeh, J. (2020). A novel mathematical model for municipal waste collection and energy generation: Case study of Kermanshah city. Management of Environmental Quality, 31(5), 1437-1453.
Xu, Y., Huang, G. H., Qin, X. S. & Cao, M. F. (2009). A stochastic robust chance-constrained programming model for municipal solid waste management under uncertainty. Resources, Conservation and Recycling, 53(6), 352-363.
Yadav, V., Karmakar, S., Dikshit, A. K., Bhurjee A. K. (2018). Interval-valued facility location model: An appraisal of municipal solid waste management system. Journal of Cleaner Production, 17110, 250-263.
 Zhang, X., Huang, G. (2014). Municipal solid waste management planning considering greenhouse gas emission trading under fuzzy environment. Journal of Environmental Management, 135, 11–18.
Zsigraiova, Z., Semiao, V. & Beijoco, F. (2013). Operation costs and pollutant emissions reduction by definition of new collection scheduling and optimization of municipal solid waste collection routes using GIS. The case study of Barreiro, Portugal. Waste Manage., 33, 793–806.