Sustainable development-oriented location-transportation integrated optimization problem regarding multi-period multi-type disaster medical waste during COVID-19 pandemic

Cejun Cao, Juan Li, Ju Liu, Jiahui Liu, Hanguang Qiu () and Jie Zhen ()
Additional contact information
Cejun Cao: Chongqing Technology and Business University
Juan Li: Chongqing Technology and Business University
Ju Liu: South China University of Technology
Jiahui Liu: Chongqing Technology and Business University
Hanguang Qiu: Chongqing Technology and Business University
Jie Zhen: Chongqing Technology and Business University

Annals of Operations Research, 2024, vol. 335, issue 3, No 18, 1447 pages

Abstract: Abstract After the outbreak of COVID-19 pandemic, devising an effective reverse logistics supply chain to clean up disaster medical waste is conducive to controlling and containing novel coronavirus transmission. Thus, the focus of this paper concentrates on multi-period multi-type disaster medical waste location-transportation integrated optimization problem with the concern of sustainability, which is formulated as a tri-objective mixed-integer programming model with the goals of maximizing total economic benefits, minimizing total carbon emissions and total potential social risks. Then, a real-world case from Wuhan using CPLEX solver is used to validate the developed model. Results indicate that constructing DMWTTSs with flexible capacity in different periods is encouraged to handle the sharply increasing disaster medical waste. The multi-period decision model outperforms the single-period one in disaster medical waste supply chains because the former has the capability of handling the uncertainties in the future periods. Increasingly, since the increase of budget doesn’t always work well and social resources are limited, the estimation of minimum budget to obtain optimum overall performance is of great importance.

Keywords: Disaster medical waste; COVID-19 pandemic; Sustainable development; Multi-period multi-type location-transportation; Multi-objective mixed-integer programming model (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10479-022-04820-2 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:annopr:v:335:y:2024:i:3:d:10.1007_s10479-022-04820-2

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10479

DOI: 10.1007/s10479-022-04820-2

Access Statistics for this article

Annals of Operations Research is currently edited by Endre Boros

More articles in Annals of Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().