Abstract
The growing use of agrochemicals added to the harm that contaminated containers cause to the environment and to the health of the population, make it necessary to establish a reverse supply chain for the recovery and correct treatment of empty containers. Current regulations establish that they must be triple-rinsed and sent to collection centers, where containers are consolidated and shipped to treatment/recycling plants. Containers can also be sent to these plants directly. Given this problem, this contribution proposes an MILP multi-period model to define the optimal configuration and operation of the reverse supply chain network of empty agrochemical containers along a given planning horizon. Provided a superstructure including farms and the location of the potential nodes (collection centers and plastic treatment plants), the model determines which facilities to install and when, their corresponding sizes, as well as how they would operate along the planning horizon. In addition, the model establishes the material flows among the various nodes in each planning period (network topology). The proposed model has been verified by addressing a realistic case study, which has been solved under different scenarios, exhibiting good computational performance. The obtained results allow reaching satisfactory conclusions in relation to model scalability and sensitivity.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Dekker, R., Fleischmann, M., Inderfurth, K., Van Wassenhove, L.: Reverse Logistics Quantitative Models for Closed-Loop Supply Chains. Springer Verlag, Berlin (2004). https://doi.org/10.1007/978-3-540-24803-3
Melo, M., Nickel, S., Saldanha-da-Gama, F.: Facility location and supply chain management - a review. Eur. J. Oper. Res. 196, 401–412 (2009). https://doi.org/10.1016/j.ejor.2008.05.007
Mota, B., Gomes, M., Carvalho, A., Barbosa-Povoa, A.: Towards supply chain sustainability: economic, environmental and social design and planning. J. Clean. Prod. 105, 14–27 (2015). https://doi.org/10.1016/j.jclepro.2014.07.052
Salema, M.G., Barbosa-Povoa, A., Novais, A.: An optimization model for the design of a capacitated multi-product reverse logistics network with uncertainty. Eur. J. Oper. Res. 179, 1063–1077 (2007). https://doi.org/10.1016/j.ejor.2005.05.032
Alumur, S., Nickel, S., Saldanha-da-Gama, F., Verter, V.: Multi-period reverse logistics network design. Eur. J. Oper. Res. 220, 67–78 (2012). https://doi.org/10.1016/j.ejor.2011.12.045
Banguera, L., Sepúlveda, J., Ternero, R., Vargas, M., Vásquez, O.: Reverse logistics network design under extended producer responsibility: the case of out-of-use tires in the Gran Santiago city of Chile. Int. J. Prod. Econ. 205, 193–200 (2018). https://doi.org/10.1016/j.ijpe.2018.09.006
Lagarda-Leyva, E.A., Morales-Mendoza, L.F., Ríos-Vázquez, N.J., et al.: Managing plastic waste from agriculture through reverse logistics and dynamic modeling. Clean Technol. Environ. Policy 21, 1415–1432 (2019). https://doi.org/10.1007/s10098-019-01700-5
Sorichetti, A., Mammini, L., Savoretti, A., Bandoni, A.: Gestión de envases vacíos de agroquímicos, dos propuestas para el Sudoeste Bonaerense. Simposio Argentino de Informática Industrial e Investigación Operativa, pp. 55–70, Buenos Aires (2018)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Yossen, G.N., Henning, G.P. (2021). Optimal Reverse Supply Chain Design: The Case of Empty Agrochemical Containers. In: Rossit, D.A., Tohmé, F., Mejía Delgadillo, G. (eds) Production Research. ICPR-Americas 2020. Communications in Computer and Information Science, vol 1407. Springer, Cham. https://doi.org/10.1007/978-3-030-76307-7_1
Download citation
DOI: https://doi.org/10.1007/978-3-030-76307-7_1
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-76306-0
Online ISBN: 978-3-030-76307-7
eBook Packages: Computer ScienceComputer Science (R0)