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

Cejun Cao; Yuting Xie; Yang Liu; Jiahui Liu; Fanshun Zhang

doi:10.1016/j.jclepro.2023.135985

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

J Clean Prod. 2023 Feb 20:389:135985. doi: 10.1016/j.jclepro.2023.135985. Epub 2023 Jan 11.

Authors

Cejun Cao^{1

2}, Yuting Xie², Yang Liu^{3

4}, Jiahui Liu⁵, Fanshun Zhang⁶

Affiliations

¹ Collaborative Innovation Center for Chongqing's Modern Trade Logistics & Supply Chain, School of Management Science and Engineering, Chongqing Technology and Business University, Chongqing, 400067, PR China.
² School of Management Science and Engineering, Chongqing Technology and Business University, Chongqing, 400067, PR China.
³ Department of Management and Engineering, Linköping University, SE-581 83 Linköping, Sweden.
⁴ Industrial Engineering and Management, University of Oulu, 90570 Oulu, Finland.
⁵ School of Business Administration, Chongqing Technology and Business University, Chongqing, 400067, PR China.
⁶ School of Business, Xiangtan University, Xiangtan, 411105, PR China.

Abstract

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.

Keywords: COVID-19 medical waste; Infection probability; Lexicographic optimisation approach; Mixed-integer programming model; Sustainability; Two-phase transport optimisation.