Sina AbbasiSara DamavandiAmir Hossien RadmankianKian ZeinolabedinzadehYigit Kazancoglu2025-10-062025259012302590-123010.1016/j.rineng.2025.104770https://www.scopus.com/inward/record.uri?eid=2-s2.0-105002633227&doi=10.1016%2Fj.rineng.2025.104770&partnerID=40&md5=9b4ba7f09c9658e207af30868ac86ca0https://gcris.yasar.edu.tr/handle/123456789/8007This 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 large-scale 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. © 2025 Elsevier B.V. All rights reserved.EnglishEnvironmental Engineering, Green Logistics Network, Mixed-integer Linear Programming, Recovery Challenges, Waste Management, Coronavirus, Integer Linear Programming, Integer Programming, Linear Programming, Mixed-integer Linear Programming, Waste Disposal, Backup Suppliers, Coronaviruses, Forward Logistics, Green Logistic Network, Green Logistics, Integer Linear Programming, Logistics Network, Mixed Integer Linear, Recovery Challenge, Reverse Logistic NetworksCoronavirus, Integer linear programming, Integer programming, Linear programming, Mixed-integer linear programming, Waste disposal, Backup suppliers, Coronaviruses, Forward logistics, Green logistic network, Green logistics, Integer Linear Programming, Logistics network, Mixed integer linear, Recovery challenge, Reverse logistic networksArticle