A multi-objective and multi-period optimization model for urban healthcare waste’s reverse logistics network design

Wang, Zhiguo; Huang, Lufei; He, Cici Xiao

doi:10.1007/s10878-019-00499-7

Cited by 38 publications

(31 citation statements)

References 51 publications

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“…Thakur and Anbanandam [41] studied the barriers of medical waste reverse logistics in India with a fuzzy-matrice d'impacts croisés multiplication appliquée á un classement (MICMAC) analysis. Wang, et al [42] proposed a bi-objective mixed integer program combined with a Grey prediction model for reverse logistics network design of medical waste, which aims at minimizing both operating cost and environmental risk. The two objective functions were combined with a weighted sum and the model was validated with a real-world case study in Shanghai, China.…”

Section: Reverse Logistics Models For Medical Wastementioning

confidence: 99%

“…Medical waste refers to the waste materials generated due to healthcare activities from hospitals, clinics, laboratories as well as other healthcare and research institutions [42,43]. The composition of medical waste may include infectious waste, sharp object, chemical substance, pathological waste, radioactive waste, etc.…”

Section: Problem Descriptionmentioning

confidence: 99%

“…Reverse logistics network design for medical waste management has been formulated by several researches [42]. The problem is usually modeled as a two-stage decision-making problem where the first stage decisions select the strategic locations for different facilities and the second stage decisions determine the operations of the network in a short-term horizon.…”

Section: Problem Descriptionmentioning

confidence: 99%

“…The problem is usually modeled as a two-stage decision-making problem where the first stage decisions select the strategic locations for different facilities and the second stage decisions determine the operations of the network in a short-term horizon. The focus is to balance the trade-off between economic performance and environmental risk related to collection, transportation, treatment and disposal of medical waste [42]. However, when an epidemic disease breaks out, the generation of infectious medical waste as well as the other healthcare hazards may be drastically increased within a very short period due to the exponentially rapid spread of the disease at the initial stage.…”

Section: Problem Descriptionmentioning

confidence: 99%

“…However, the fly ash, SO2 as well as other pollutants from the incineration of medical waste may result in air pollution and an improper location of incineration plant may hence impose a significant risk on nearby residents [49]. Reverse logistics network design for medical waste management has been formulated by several researches [42]. The problem is usually modeled as a two-stage decision-making problem where the first stage decisions select the strategic locations for different facilities and the second stage decisions determine the operations of the network in a short-term horizon.…”

Section: Problem Descriptionmentioning

confidence: 99%

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Reverse Logistics Network Design for Effective Management of Medical Waste in Epidemic Outbreaks: Insights from the Coronavirus Disease 2019 (COVID-19) Outbreak in Wuhan (China)

Sun

Solvang

et al. 2020

IJERPH

275

234

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The outbreak of an epidemic disease may pose significant treats to human beings and may further lead to a global crisis. In order to control the spread of an epidemic, the effective management of rapidly increased medical waste through establishing a temporary reverse logistics system is of vital importance. However, no research has been conducted with the focus on the design of an epidemic reverse logistics network for dealing with medical waste during epidemic outbreaks, which, if improperly treated, may accelerate disease spread and pose a significant risk for both medical staffs and patients. Therefore, this paper proposes a novel multi-objective multi-period mixed integer program for reverse logistics network design in epidemic outbreaks, which aims at determining the best locations of temporary facilities and the transportation strategies for effective management of the exponentially increased medical waste within a very short period. The application of the model is illustrated with a case study based on the outbreak of the coronavirus disease 2019 in Wuhan, China. Even though the uncertainty of the future COVID-19 spread tendency is very high at the time of this research, several general policy recommendations can still be obtained based on computational experiments and quantitative analyses. Among other insights, the results suggest installing temporary incinerators may be an effective solution for managing the tremendous increase of medical waste during the COVID-19 outbreak in Wuhan, but the location selection of these temporary incinerators is of significant importance. Due to the limitation on available data and knowledge at present stage, more real-world information are needed to assess the effectiveness of the current solution.

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Section: Reverse Logistics Models For Medical Wastementioning

confidence: 99%

Section: Problem Descriptionmentioning

confidence: 99%

Section: Problem Descriptionmentioning

confidence: 99%

Section: Problem Descriptionmentioning

confidence: 99%

Section: Problem Descriptionmentioning

confidence: 99%

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