Title:
Resilience Assessment of Hyperconnected Parcel Logistic Networks Under Worst-Case Disruptions
Resilience Assessment of Hyperconnected Parcel Logistic Networks Under Worst-Case Disruptions
Author(s)
Kulkarni, Onkar
Dahan, Mathieu
Montreuil, Benoit
Dahan, Mathieu
Montreuil, Benoit
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Abstract
Logistics networks that shape the Physical Internet’s logistics web are prone to potentially adversarial disruptions that impact their performance severely. In this article, we study a network interdiction problem on a multi-commodity flow network in which an adversary totally disrupts a set of network arcs with an intention to maximize the operational costs of delivering parcels. We formulate it as a two-stage mixed-integer linear program. To solve such complex large-scale program, we use linear programming duality and provide an algorithm based on the structure of the program that computes the set of network arcs that can be interdicted in order to reduce its size. Finally, we use the model and solution framework to evaluate the resilience capabilities of topology optimized hyperconnected networks and compare it with lean networks. We find that our developed solution methodology reduces the size of network interdiction program substantially and showcases superior computational performance against off-the-shelf optimization solvers. Furthermore, the resilience comparison between hyperconnected networks and lean networks depicts enhanced capabilities of the topology optimized hyperconnected networks to sustain worst-case disruptive events as opposed to that of lean logistics networks.
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Date Issued
2023-06
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