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    Highlights A direct and reverse sustainable COVID-19 vaccine supply chain network is designed. Fuzzy time window-based VRP has also been considered in the proposed model. The proposed fuzzy multi-objective model is optimized using three approaches. Time flexibility could result in rising satisfaction by 16.16% with a green impact.

    Abstract Due to the unforeseen outcomes of the recent COVID-19 pandemic, the adoption of essential policies and tactics to implement public vaccination programs has gained attention worldwide. Statistics indicate that medical waste production is growing dramatically, posing a major risk to both individuals and the environment if not properly handled. In this context, we present a sustainable fuzzy multi-objective, multi-period, multi-product, and location-allocation model that considers both the vaccine distribution phase and the medical waste management process. The model addresses the capacitated and multi-depot vehicle routing problem (VRP) with heterogeneous vehicles. Moreover, as a new social aspect from vaccination centers’ perspective, a fuzzy version of the time-window is considered in the model to integrate both satisfaction level and priority of the nodes that must be visited. Subsequently, the augmented ε-constraint, TH method, and LP-Metric approach are utilized to solve the proposed multi-objective model. To provide empirical support for the model’s input parameters and evaluate the effectiveness of the solution strategies, data for a medical supply chain network (MSCN) in Iran is used. The results demonstrate that shifting the vaccination centers’ desired time to be serviced might be a suitable solution to stop the emission rate from increasing or the satisfaction levels from falling.


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    Titel :

    Optimal distribution and waste management of Covid-19 vaccines from vaccination centers’ satisfaction perspective – A fuzzy time window-based VRP


    Beteiligte:
    Maleki, Abolfazl (Autor:in) / Hemmati, Vahid (Autor:in) / Reza Abazari, Seyed (Autor:in) / Aghsami, Amir (Autor:in) / Rabbani, Masoud (Autor:in)


    Erscheinungsdatum :

    2024-02-04




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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