A Bi-objective location-routing model for the healthcare waste management in the era of logistics 4.0 under uncertainty
The purpose of this study is to apply Industry 4.0-based technologies to improve the management of infectious healthcare waste considering location-routing problem and population risk under uncertainty. To achieve this, a decision support system is developed and implemented utilizing a bi-objective...
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| Vydáno v: | International journal of production economics Ročník 276; s. 109342 |
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| Hlavní autoři: | , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Elsevier B.V
01.10.2024
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| Témata: | |
| ISSN: | 0925-5273, 1873-7579 |
| On-line přístup: | Získat plný text |
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| Abstract | The purpose of this study is to apply Industry 4.0-based technologies to improve the management of infectious healthcare waste considering location-routing problem and population risk under uncertainty. To achieve this, a decision support system is developed and implemented utilizing a bi-objective mixed-integer linear programming (MILP) model. The bi-objective MILP model improves the performance of the healthcare waste management by applying Industry 4.0 technologies, including electric autonomous vehicles, information sharing system, internet of things (IoT), Global Navigation Satellite System (GNSS), and RFID-tagged waste bags. We develop a multi-objective solution approach by integrating the lexicographic and TH methods. The validity of the model has been established through its implementation in seven hospitals in the city of Karaj, Iran. The results denoted significant improvements in waste collection efficiency, route optimization, and the reduction of contamination risks. |
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| AbstractList | The purpose of this study is to apply Industry 4.0-based technologies to improve the management of infectious healthcare waste considering location-routing problem and population risk under uncertainty. To achieve this, a decision support system is developed and implemented utilizing a bi-objective mixed-integer linear programming (MILP) model. The bi-objective MILP model improves the performance of the healthcare waste management by applying Industry 4.0 technologies, including electric autonomous vehicles, information sharing system, internet of things (IoT), Global Navigation Satellite System (GNSS), and RFID-tagged waste bags. We develop a multi-objective solution approach by integrating the lexicographic and TH methods. The validity of the model has been established through its implementation in seven hospitals in the city of Karaj, Iran. The results denoted significant improvements in waste collection efficiency, route optimization, and the reduction of contamination risks. The purpose of this study is to apply Industry 4.0-based technologies to improve the management of infectious healthcare waste considering location-routing problem and population risk under uncertainty. To achieve this, a decision support system is developed and implemented utilizing a bi-objective mixed-integer linear programming (MILP) model. The bi-objective MILP model improves the performance of the healthcare waste management by applying Industry 4.0 technologies, including electric autonomous vehicles, information sharing system, internet of things (IoT), Global Navigation Satellite System (GNSS), and RFID-tagged waste bags. We develop a multiobjective solution approach by integrating the lexicographic and TH methods. The validity of the model has been established through its implementation in seven hospitals in the city of Karaj, Iran. The results denoted significant improvements in waste collection efficiency, route optimization, and the reduction of contamination risks. |
| ArticleNumber | 109342 |
| Author | Govindan, Kannan Mina, Hassan Sorooshian, Shahryar Naieni Fard, Fereshteh Sadeghi Asgari, Fahimeh |
| Author_xml | – sequence: 1 givenname: Kannan surname: Govindan fullname: Govindan, Kannan email: kannan.govindan@adelaide.edu.au organization: China Institute of FTZ Supply Chain, Shanghai Maritime University, Shanghai, China – sequence: 2 givenname: Fereshteh Sadeghi surname: Naieni Fard fullname: Naieni Fard, Fereshteh Sadeghi organization: Department of Information Science, University of North Texas, Denton, TX76207, USA – sequence: 3 givenname: Fahimeh surname: Asgari fullname: Asgari, Fahimeh organization: Department of Information Technology and Decision Science, G. Brint Ryan College of Business, University of North Texas, USA – sequence: 4 givenname: Shahryar orcidid: 0000-0001-5336-827X surname: Sorooshian fullname: Sorooshian, Shahryar organization: Department of Business Administration, University of Gothenburg, Gothenburg, Sweden – sequence: 5 givenname: Hassan surname: Mina fullname: Mina, Hassan organization: Prime School of Logistics, Saito University College, Petaling Jaya, Selangor, Malaysia |
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| Keywords | Location-routing problem Healthcare waste management Logistics 4.0 Electric autonomous vehicle Fuzzy theory |
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| SubjectTerms | Economics and Business Ekonomi och näringsliv Electric autonomous vehicle Fuzzy theory Healthcare waste management Location-routing problem Logistics 4.0 |
| Title | A Bi-objective location-routing model for the healthcare waste management in the era of logistics 4.0 under uncertainty |
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