Designing a green forward and reverse logistics network with an IoT approach considering backup suppliers and special disposal for epidemics management
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Date
2025
Authors
Sina Abbasi
Sara Damavandi
Amirhossein Radmankian
Kian Zeinolabedinzadeh
Yigit Kazancoglu
Journal Title
Journal ISSN
Volume Title
Publisher
ELSEVIER
Open Access Color
GOLD
Green Open Access
No
OpenAIRE Downloads
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Publicly Funded
No
Abstract
This paper proposes a mathematical model for the green forward and reverse logistics network (LN) examining the impact of epidemics such as coronavirus (COVID-19) and human metapneumovirus (HMPV) on this network. Alongside managing the network a new support center and dedicated infectious waste recycling and disposal facilities have been established. A mixed-integer linear programming (MOMILP) approach is employed for modeling a green forward and reverse LN during epidemics. This study presents two problem-solving techniques: the LP-metric method for small problems and the whale optimization algorithm (WOA) for medium and largescale issues. The positive and negative effects of epidemics on environmental and economic aspects of the objective functions were assessed. This study's contribution and novelty compared to previous research lie in the introduction of backup supply centers particularly waste disposal centers and the comparison of normal and epidemic conditions for disaster management using the IoT approach.
Description
Keywords
Green logistics network, Recovery challenges, Waste management, Environmental engineering, Mixed-integer linear programming, HUMAN METAPNEUMOVIRUS, MODEL, Environmental Engineering, Waste Management, Green Logistics Network, Mixed-Integer Linear Programming, Recovery Challenges, Technology, Recovery challenges, Mixed-integer linear programming, T, Environmental engineering, Waste management, Green logistics network
Fields of Science
Citation
WoS Q
Scopus Q

OpenCitations Citation Count
4
Source
Results in Engineering
Volume
26
Issue
Start Page
104770
End Page
PlumX Metrics
Citations
CrossRef : 4
Scopus : 9
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Mendeley Readers : 60
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