Modeling Shock Propagation on Supply Chain Networks: A Stochastic Logistic-Type Approach
| Autor: | Danilo Liuzzi, Iside Rita Laganà, Cinzia Colapinto, Davide La Torre |
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| Rok vydání: | 2021 |
| Předmět: |
Flexibility (engineering)
Settore SECS-S/06 - Metodi mat. dell'economia e Scienze Attuariali e Finanziarie Social distance media_common.quotation_subject Supply chain Control (management) Vulnerability COVID-19 Networks Stochastic disruption shocks Stochastic logistics Settore SECS-P/08 - Economia e Gestione delle Imprese Adaptability Risk analysis (engineering) Global network Relevance (information retrieval) Business media_common |
| Zdroj: | Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems ISBN: 9783030859091 APMS (4) |
| DOI: | 10.1007/978-3-030-85910-7_3 |
| Popis: | Supply Chains have been more and more suffering from unexpected industrial, natural events, or epidemics that might disrupt the normal flow of materials, information, and money. The recent pandemic triggered by the outbreak of the new COVID-19 has pointed out the increasing vulnerability of supply chain networks, prompting companies (and governments) to implement specific policies and actions to control and reduce the spread of the disease across the network, and to cope with exogenous shocks. In this paper, we present a stochastic Susceptible-Infected-Susceptible (SIS) framework to model the spread of new epidemics across different distribution networks and determine social distancing/treatment policies in the case of local and global networks. We highlight the relevance of adaptability and flexibility of decisions in unstable and unpredictable scenarios. |
| Databáze: | OpenAIRE |
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