A multi-objective sustainable supply chain network design problem for perishable foods

Document Type : Research Paper


School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran


Increasing demand for food, environmental degradation, postharvest losses, and lack of financial resources, especially in developing countries, encourage manufacturing supply chains to develop integrated decision models for jointly incorporating economic, environmental, and social aspects into the supply chain network design problems. This research aims to develop a novel multi-objective decision support model for designing a sustainable multi-product green supply chain network for perishable food products. The model aims to minimize the total costs and carbon dioxide emissions while maximizing the social impacts simultaneously. Numerical experiments on several test problems indicate that the total cost is mostly impacted by the fixed cost of constructing warehouses and maintenance costs, respectively. The total amount of carbon emissions is more influenced by the amount of carbon produced in warehouses than transportation activities. We also found that the number of jobs created plays a much more critical role on social satisfaction than the amount of traffic generated by the supply chain. Also, the number of jobs created and the amount of carbon gas produced in the warehouses have a direct relationship; therefore, these two factors should be considered together simultaneously in the supply chain network design problem.


Main Subjects

Behzadi, G. et al. (2017) ‘Robust and resilient strategies for managing supply disruptions in an agribusiness supply chain’, International Journal of Production Economics, 191, pp. 207–220.
Biuki, M., Kazemi, A. and Alinezhad, A. (2020) ‘An integrated location-routing-inventory model for sustainable design of a perishable products supply chain network’, Journal of Cleaner Production, 260, p. 120842.
Bloemhof, J. M. and Soysal, M. (2017) ‘Sustainable food supply chain design’, in Sustainable Supply Chains. Springer, pp. 395–412.
Bortolini, M. et al. (2016) ‘Fresh food sustainable distribution: cost, delivery time and carbon footprint three-objective optimization’, Journal of Food Engineering, 174, pp. 56–67.
Chang, C.-T. (2007) ‘Multi-choice goal programming’, Omega, 35(4), pp. 389–396.
Chang, C.-T. (2008) ‘Revised multi-choice goal programming’, Applied mathematical modelling, 32(12), pp. 2587–2595.
Colicchia, C. et al. (2016) ‘Eco-efficient supply chain networks: development of a design framework and application to a real case study’, Production Planning & Control, 27(3), pp. 157–168. doi: 10.1080/09537287.2015.1090030.
Dutta, P. and Shrivastava, H. (2020) ‘The design and planning of an integrated supply chain for perishable products under uncertainties’, Journal of Modelling in Management.
Eskandarpour, M. et al. (2015) ‘Sustainable supply chain network design: An optimization-oriented review’, Omega, 54, pp. 11–32.
Ghezavati, V. R., Hooshyar, S. and Tavakkoli-Moghaddam, R. (2017) ‘A Benders’ decomposition algorithm for optimizing distribution of perishable products considering postharvest biological behavior in agri-food supply chain: a case study of tomato’, Central European Journal of Operations Research, 25(1), pp. 29–54.
Govindan, K. et al. (2020) ‘An integrated hybrid approach for circular supplier selection and closed loop supply chain network design under uncertainty’, Journal of Cleaner Production, 242, p. 118317.
Govindan, K., Fattahi, M. and Keyvanshokooh, E. (2017) ‘Supply chain network design under uncertainty: A comprehensive review and future research directions’, European Journal of Operational Research, 263(1), pp. 108–141.
Hervani, A. A., Helms, M. M. and Sarkis, J. (2005) ‘Performance measurement for green supply chain management’, Benchmarking: An international journal.
Jouzdani, J. and Govindan, K. (2021) ‘On the sustainable perishable food supply chain network design: A dairy products case to achieve sustainable development goals’, Journal of Cleaner Production, 278, p. 123060.
Kannan, D. et al. (2020) ‘Sustainable circular supplier selection: A novel hybrid approach’, Science of the Total Environment, 722, p. 137936.
Kelle, P. et al. (2019) ‘Evaluation of operational and environmental sustainability tradeoffs in multimodal freight transportation planning’, International Journal of Production Economics, 209, pp. 411–420. doi: https://doi.org/10.1016/j.ijpe.2018.08.011.
Kovačić, D. et al. (2015) ‘Location and lead-time perturbations in multi-level assembly systems of perishable goods in Spanish baby food logistics’, Central European journal of operations research, 23(3), pp. 607–623.
Lee, S. M. (1972) Goal programming for decision analysis. Auerbach Publishers Philadelphia.
Melo, M. T., Nickel, S. and Saldanha-Da-Gama, F. (2009) ‘Facility location and supply chain management–A review’, European journal of operational research, 196(2), pp. 401–412.
Meneghetti, A. and Monti, L. (2015) ‘Greening the food supply chain: an optimisation model for sustainable design of refrigerated automated warehouses’, International Journal of Production Research, 53(21), pp. 6567–6587.
Mogale, D. G., Cheikhrouhou, N. and Tiwari, M. K. (2020) ‘Modelling of sustainable food grain supply chain distribution system: a bi-objective approach’, International Journal of Production Research, 58(18), pp. 5521–5544.
Mohammed, A. and Wang, Q. (2017a) ‘Developing a meat supply chain network design using a multi-objective possibilistic programming approach’, British Food Journal.
Mohammed, A. and Wang, Q. (2017b) ‘The fuzzy multi-objective distribution planner for a green meat supply chain’, International Journal of Production Economics, 184, pp. 47–58.
Musavi, M. and Bozorgi-Amiri, A. (2017) ‘A multi-objective sustainable hub location-scheduling problem for perishable food supply chain’, Computers & Industrial Engineering, 113, pp. 766–778. doi: https://doi.org/10.1016/j.cie.2017.07.039.
Nayeri, S. et al. (2020) ‘Multi-objective fuzzy robust optimization approach to sustainable closed-loop supply chain network design’, Computers & Industrial Engineering, 148, p. 106716.
Rashidi, K. et al. (2020) ‘Applying the triple bottom line in sustainable supplier selection: A meta-review of the state-of-the-art’, Journal of Cleaner Production, p. 122001.
Sazvar, Z. et al. (2014) ‘A bi-objective stochastic programming model for a centralized green supply chain with deteriorating products’, International Journal of Production Economics, 150, pp. 140–154.
Sazvar, Z., Rahmani, M. and Govindan, K. (2018) ‘A sustainable supply chain for organic, conventional agro-food products: The role of demand substitution, climate change and public health’, Journal of cleaner production, 194, pp. 564–583.
Song, B. D. and Ko, Y. D. (2016) ‘A vehicle routing problem of both refrigerated-and general-type vehicles for perishable food products delivery’, Journal of food engineering, 169, pp. 61–71.
Tamiz, M., Jones, D. and Romero, C. (1998) ‘Goal programming for decision making: An overview of the current state-of-the-art’, European Journal of operational research, 111(3), pp. 569–581.
Zhu, Z. et al. (2018) ‘Recent advances and opportunities in sustainable food supply chain: a model-oriented review’, International Journal of Production Research, 56(17), pp. 5700–5722.