2207. Enhancing post-disaster relief operations: a bi-objective approach to temporary logistics hubs location
Invited abstract in session MA-48: Location and Logistics, stream Locational Analysis.
Monday, 8:30-10:00Room: Parkinson B09
Authors (first author is the speaker)
| 1. | Serena Fugaro
|
| Institute for Applications of Calculus, National Research Council of Italy | |
| 2. | Antonino Sgalambro
|
| Analytics, Technology and Operations Department, Leeds University Business School |
Abstract
In post-disaster relief operations, temporary logistics hubs are essential facilities for deconsolidating, storing, consolidating, and transporting relief supplies between emergency relief providers (e.g., donors, government warehouses) and affected areas. In this work, we propose a novel Bi-Objective Capacitated Multiple Allocation Hub Location problem with Splittable Demand to address the hub-and-spoke network design problem associated with humanitarian logistics in post-disaster environments. The decisions to be made are: where to locate the temporary logistics hubs, and the amount of flow of each relief material that should traverse the available network links to ensure timely aid. Two objectives are considered to assess the performance of the designed network: minimising the average arrival time of the flows and minimising the latest arrival time. Indeed, whilst time is a crucial factor in post-disaster operations management, it has received limited attention in humanitarian logistics problems in terms of modelling tools explicitly employed to ensure its adequate representation. In order to fill this gap, in this work we make use of Flows over Time. Uncertainty is an inherent part of a humanitarian logistics system due to the different levels of accuracy of its parameters; to represent this aspect, we use ad hoc modelling tools. We also propose algorithmic approaches to mitigate the uncertainty while providing valuable decision support in post-disaster relief operations.
Keywords
- Location
- Humanitarian Applications
- Multi-Objective Decision Making
Status: accepted
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