A novel cooperative model in the collection of infectious waste in COVID-19 pandemic
Journal of Modelling in Management
ISSN: 1746-5664
Article publication date: 1 March 2021
Issue publication date: 17 February 2022
Abstract
Purpose
Production of waste has been increased exponentially due to world industrialization and urban and machine life expansion. On the other hand, the outbreak of the COVID-19 coronavirus quickly became a global crisis. This crisis has added a large amount of waste to urban waste. The purpose of this study is to create cooperation between municipal waste collector contractors.
Design/methodology/approach
Thus, a mathematical model is proposed under uncertain conditions, which includes the volume of municipal waste and infectious waste including personal protective equipment and used equipment for patients. To reduce total costs, the results are evaluated with four cooperative game theory methods such as Shapley value, t value, core center and least core. Ultimately, the saved cost by cooperation in each coalition is allocated fairly among the contractors. Finally, a comparison was made between the solution methods based on the value of the objective function and the solution time.
Findings
The results indicate that the proposed cooperative method increases cost savings and reduces the fine of residual waste. Therefore, it can be mentioned that this kind of cooperation would finally result in more incentives for contractors to form larger coalitions. Genetic algorithms were used to solve the large-scale model.
Originality/value
The proposed model boosts the current understanding of waste management in the COVID-19 pandemic. The paper adds additional value by unveiling some key future research directions. This guidance may demonstrate possible existing and unexplored gaps so that researchers can direct future research to develop new processes.
Keywords
Citation
Valizadeh, J. and Mozafari, P. (2022), "A novel cooperative model in the collection of infectious waste in COVID-19 pandemic", Journal of Modelling in Management, Vol. 17 No. 1, pp. 363-401. https://doi.org/10.1108/JM2-07-2020-0189
Publisher
:Emerald Publishing Limited
Copyright © 2021, Emerald Publishing Limited