Two-phase COVID-19 medical waste transport optimisation considering sustainability and infection probability

• Published in: Journal of cleaner production Vol. 389; p. 135985
• Main Authors: Cao, Cejun, Xie, Yuting, Liu, Yang, Liu, Jiahui, Zhang, Fanshun
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier Ltd 20.02.2023; The Authors. Published by Elsevier Ltd
• Subjects: case studies; COVID-19 infection; COVID-19 medical waste; economic sustainability; Infection probability; Lexicographic optimisation approach; Mixed-integer programming model; Orthocoronavirinae; risk; society; Sustainability; Two-phase transport optimisation; Infection probability; Mixed-integer programming model; COVID-19 medical waste; Two-phase transport optimisation; Sustainability; Lexicographic optimisation approach; Mixed -integer programming model
• ISSN: 0959-6526; 1879-1786; 1879-1786
• DOI: 10.1016/j.jclepro.2023.135985

A safe and effective medical waste transport network is beneficial to control the COVID-19 pandemic and at least decelerate the spread of novel coronavirus. Seldom studies concentrated on a two-phase COVID-19 medical waste transport in the presence of multi-type vehicle selection, sustainability, and infection probability, which is the focus of this paper. This paper aims to identify the priority of sustainable objectives and observe the impacts of multi-phase and infection probability on the results. Thus, such a problem is formulated as a mixed-integer programming model to minimise total potential infection risks, minimise total environmental risks, and maximise total economic benefits. Then, a hybrid solution strategy is designed, incorporating a lexicographic optimisation approach and a linear weighted sum method. A real-world case study from Chongqing is used to illustrate this methodology. Results indicate that the solution strategy guides a good COVID-19 medical waste transport scheme within 1 min. The priority of sustainable objectives is society, economy, and environment in the first and second phases because the total Gap of case No.35 is 3.20%. A decentralised decision mode is preferred to design a COVID-19 medical waste transport network at the province level. Whatever the infection probability is, infection risk is the most critical concern in the COVID-19 medical waste clean-up activities. Environmental and economic sustainability performance also should be considered when infection probability is more than a certain threshold. •Two-phase COVID-19 medical waste transport with infection probability is studied.•A mixed-integer programming model to optimise sustainability is formulated.•A hybrid solution strategy is designed to solve the proposed multi-objective model.•The priority of sustainable objectives is society, economy, and environment.