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3296. Fleet Composition and Scheduling for Provision of En-Route Relief Aid Using an Adaptive Large Neighborhood Search with Decisions on the Intensive Margin
Invited abstract in session WA-21: Post-Disaster Relief Distribution, stream OR in Humanitarian Operations (HOpe).
Wednesday, 8:30-10:00Room: 49 (building: 116)
Authors (first author is the speaker)
| 1. | Lars Päsler
|
| Universiteit van Amsterdam | |
| 2. | Merel Groen
|
| 3. | Lisanne van Rijn
|
| Rotterdam School of Management |
Abstract
Refugees need periodic relief aid along their routes to safe places. To this end, continuation of service is crucial to alleviate their mental and physical burden. It has been shown that employing mobile facilities over fixed facilities to provide relief aid can reduce costs. The challenge in coordinating the number and schedules of mobile facilities has been formulated in the multi-period mobile facility location problem with mobile demand (MM-FLP-MD). Our research aims to determine the impact of using a fleet of different facility types and introducing capacity and duration constraints for facilities. We compare solutions from a Mixed Integer Linear Programming model and an Adaptive Large Neighborhood Search (ALNS). A prior proposed ALNS is enriched with additional operators and we exploit the problem’s structure to permit a two-step repair procedure. Moreover, we discuss the application of an ALNS for decisions on the intensive margin, i.e. to make decisions from a non-binary decision space. This methodology is applied in a case study of the Western Balkan route during the 2015 European refugee crisis. We find that some of our operators provide similar improvements at a lower computational cost compared to the best operators in previous literature and some decision variables lie indeed on the intensive margin. An insight for humanitarian organizations is to use more smaller facilities in optimistic cost scenarios and favor larger facilities in more pessimistic scenarios.
Keywords
- Disaster and Crisis Management
- Humanitarian Applications
- Metaheuristics
Status: accepted
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