  Modern logistics systems worldwide are facing unprecedented challenges due to
the explosive growth of e-commerce, driving the need for resilient systems to
tackle problems such as vulnerable supplies, volatile demands, and fragile
transportation networks. Motivated by the innovative concept of the Physical
Internet, this paper focuses on resilient capacity deployment of open-access
logistics hubs in hyperconnected transportation under demand uncertainty and
geographical disruptions. We propose a two-stage stochastic optimization model,
aiming to smartly deploy the hub capacity to achieve delivery timeliness, high
consolidation and network resilience while minimizing hub set-up budget and
truck fleet cost. Four optimal hub network configurations are derived by
applying scenarios at four stress testing levels into the optimization model,
including deterministic demands without hub disruptions, deterministic demands
with hub disruptions, stochastic demands without hub disruptions as well as
stochastic demands with hub disruptions. To test the performances of different
optimal networks, a simulation-based study is then performed over an automotive
delivery-to-dealer network and dataset in the Southeast US region. Our results
demonstrate the key impacts of various uncertainties on hub capacity deployment
in terms of capacity configuration distribution, network resilience, delivery
timeliness, and cost-effectiveness. Overall, this study provides a reliable
network capacity deployment approach with persistent and sustainable economic
and social performances in hyperconnected networks, and the results validate
the relationship between capacity deployment and network resilience under
different types of uncertainties.
