Solving facility location problems for disaster response using simheuristics and survival analysis: a hybrid modeling approach
Solving facility location problems for disaster response using simheuristics and survival analysis: a hybrid modeling approach
One of the important decisions for mitigating the risk from a sudden onset disaster is to determine the optimal location of relevant facilities (e.g., warehouses), because this affects the subsequent humanitarian operations. Researchers have proposed several methods to solve the facility location problem (FLP) in disaster management. This paper considers a stochastic FLP where the goal is to minimize the expected time required to provide service to all affected regions when travel times are stochastic due to uncertain road conditions. The number of facilities to open is constrained by a certain maximum budget. To solve this stochastic optimization problem, we propose a hybrid simulation optimization model that combines a simheuristic algorithm with a survival analysis method to evaluate the probability of meeting the demand of all affected areas within a time target. An experiment using a benchmark set shows our model outperforms deterministic solutions by about 8.9%.
1497-1508
Onggo, Bhakti Stephan
8e9a2ea5-140a-44c0-9c17-e9cf93662f80
Martin, Xabier
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Panadero, Javier
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Corlu, Canan Gunes
ecb0f999-21d4-41e2-8cab-58a33706f09e
Juan, Angel A.
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11 December 2022
Onggo, Bhakti Stephan
8e9a2ea5-140a-44c0-9c17-e9cf93662f80
Martin, Xabier
57abfc12-fb4d-4477-982e-4faafb53550f
Panadero, Javier
2dca23fd-f7e1-491a-a9c0-a72f901c76e1
Corlu, Canan Gunes
ecb0f999-21d4-41e2-8cab-58a33706f09e
Juan, Angel A.
f8b5781e-704e-4699-9841-97ddab494d8d
Onggo, Bhakti Stephan, Martin, Xabier, Panadero, Javier, Corlu, Canan Gunes and Juan, Angel A.
(2022)
Solving facility location problems for disaster response using simheuristics and survival analysis: a hybrid modeling approach.
Feng, B., Pedrielli, G., Peng, Y., Shashaani, S., Song, E., Corlu, C.G., Lee, L.H., Chew, E.P., Roeder, T. and Lendermann, P.
(eds.)
In Proceedings of the 2022 Winter Simulation Conference, WSC 2022.
vol. 2022-December,
IEEE.
.
(doi:10.1109/WSC57314.2022.10015419).
Record type:
Conference or Workshop Item
(Paper)
Abstract
One of the important decisions for mitigating the risk from a sudden onset disaster is to determine the optimal location of relevant facilities (e.g., warehouses), because this affects the subsequent humanitarian operations. Researchers have proposed several methods to solve the facility location problem (FLP) in disaster management. This paper considers a stochastic FLP where the goal is to minimize the expected time required to provide service to all affected regions when travel times are stochastic due to uncertain road conditions. The number of facilities to open is constrained by a certain maximum budget. To solve this stochastic optimization problem, we propose a hybrid simulation optimization model that combines a simheuristic algorithm with a survival analysis method to evaluate the probability of meeting the demand of all affected areas within a time target. An experiment using a benchmark set shows our model outperforms deterministic solutions by about 8.9%.
Text
WSC2022_Simheuristics_for_Disaster_Management (1)
- Accepted Manuscript
More information
Published date: 11 December 2022
Additional Information:
Funding Information:
This research is funded by the Engineering and Physical Sciences Research Council and Global Challenges Research Fund (EP/T00360X/1) and the Spanish Ministry of Science (PID2019-111100RB-C21).
Venue - Dates:
2022 Winter Simulation Conference, WSC 2022, , Guilin, China, 2022-12-11 - 2022-12-14
Identifiers
Local EPrints ID: 475727
URI: http://eprints.soton.ac.uk/id/eprint/475727
ISSN: 0891-7736
PURE UUID: 0948e8f2-77c8-4863-9425-c0b44d76c84a
Catalogue record
Date deposited: 27 Mar 2023 16:35
Last modified: 18 Mar 2024 03:50
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Contributors
Author:
Xabier Martin
Author:
Javier Panadero
Author:
Canan Gunes Corlu
Author:
Angel A. Juan
Editor:
B. Feng
Editor:
G. Pedrielli
Editor:
Y. Peng
Editor:
S. Shashaani
Editor:
E. Song
Editor:
C.G. Corlu
Editor:
L.H. Lee
Editor:
E.P. Chew
Editor:
T. Roeder
Editor:
P. Lendermann
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