Concepts and applications of backup coverage
Management Science
Allocation of distinguishable servers
Computers and Operations Research
An overview of representative problems in location research
Management Science
Annals of Operations Research - Special issue on locational decisions
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Towards unified formulations and extensions of two classical probabilistic location models
Computers and Operations Research
Solution approaches for facility location of medical supplies for large-scale emergencies
Computers and Industrial Engineering
Survey: Covering problems in facility location: A review
Computers and Industrial Engineering
Survey: Facility location dynamics: An overview of classifications and applications
Computers and Industrial Engineering
Location allocation modeling for healthcare facility planning in Malaysia
Computers and Industrial Engineering
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The main purpose of Emergency Medical Service systems is to save lives by providing quick response to emergencies. The performance of these systems is affected by the location of the ambulances and their allocation to the customers. Previous literature has suggested that simultaneously making location and dispatching decisions could potentially improve some performance measures, such as response times. We developed a mathematical formulation that combines an integer programming model representing location and dispatching decisions, with a hypercube model representing the queuing elements and congestion phenomena. Dispatching decisions are modeled as a fixed priority list for each customer. Due to the model's complexity, we developed an optimization framework based on Genetic Algorithms. Our results show that minimization of response time and maximization of coverage can be achieved by the commonly used closest dispatching rule. In addition, solutions with minimum response time also yield good values of expected coverage. The optimization framework was able to consistently obtain the best solutions (compared to enumeration procedures), making it suitable to attempt the optimization of alternative optimization criteria. We illustrate the potential benefit of the joint approach by using a fairness performance indicator. We conclude that the joint approach can give insights of the implicit trade-offs between several conflicting optimization criteria.