Concepts and applications of backup coverage
Management Science
The capacitated maximal covering location problem with backup service
Annals of Operations Research
A new greedy approach for facility location problems
STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
On the use of genetic algorithms to solve location problems
Computers and Operations Research - Location analysis
Heuristic Methods for Large Centroid Clustering Problems
Journal of Heuristics
e-Work based collaborative optimization approach for strategic logistic network design problem
Computers and Industrial Engineering
Planar maximal covering with ellipses
Computers and Industrial Engineering
Tabu based heuristics for the generalized hierarchical covering location problem
Computers and Industrial Engineering
Survey: Covering problems in facility location: A review
Computers and Industrial Engineering
Location allocation modeling for healthcare facility planning in Malaysia
Computers and Industrial Engineering
Vulnerability based robust protection strategy selection in service networks
Computers and Industrial Engineering
Joint location and dispatching decisions for Emergency Medical Services
Computers and Industrial Engineering
Robust vertex p-center model for locating urgent relief distribution centers
Computers and Operations Research
Computers and Industrial Engineering
Determining the number of facilities for large-scale emergency
International Journal of Computing Science and Mathematics
Humanitarian/emergency logistics models: a state of the art overview
Proceedings of the 2013 Summer Computer Simulation Conference
Determination of the locations and capacities of sugar cane loading stations in Thailand
Computers and Industrial Engineering
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In this paper, we propose models and solution approaches for determining the facility locations of medical supplies in response to large-scale emergencies. We address the demand uncertainty and medical supply insufficiency by providing each demand point with services from a multiple quantity of facilities that are located at different quality levels (distances). The problem is formulated as a maximal covering problem with multiple facility quantity-of-coverage and quality-of-coverage requirements. Three heuristics are developed to solve the location problem: a genetic algorithm heuristic, a locate-allocate heuristic, and a Lagrangean relaxation heuristic. We evaluate the performance of the model and the heuristics by using illustrative emergency examples. We show that the model provides an effective method to address uncertainties with little added cost in demand point coverage. We also show that the heuristics are able to generate good facility location solutions in an efficient manner. Moreover, we give suggestions on how to select the most appropriate heuristic to solve different location problem instances.