The Mathematics of Infectious Diseases
SIAM Review
Genetic Algorithms and Simulated Annealing
Genetic Algorithms and Simulated Annealing
A discrete epidemic model for SARS transmission and control in China
Mathematical and Computer Modelling: An International Journal
A consensus problem for a class of vehicles with 2-D dynamics
Multidimensional Systems and Signal Processing
Optimal intervention policies for a multidimensional simple epidemic process
Mathematical and Computer Modelling: An International Journal
Bézier control parameterization for evolutionary optimization in disease models
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Optimal control for SIRC epidemic outbreak
Computer Methods and Programs in Biomedicine
| Hi-index | 0.98 |
This paper discusses the application of optimal and sub-optimal controls to a SEQIJR SARS model via the Pontryagin's Maximum Principle. To this end, two control variables representing the quarantine and isolation strategies are considered in the model. The numerical optimal control laws are implemented in an iterative method, and the sub-optimal solution is computed using a genetic algorithm. The simulation results demonstrate that the maximal applications of quarantining and isolation strategies in the early stage of the epidemic are of very critical impacts in both cases of optimal and sub-optimal control. Otherwise, the control effect will be much worse. This gives a theoretical interpretation to the practical experiences that the early quarantine and isolation strategies are critically important to control the outbreaks of epidemics. Furthermore, our results also show that the proposed sub-optimal control can lead to performances close to the optimal control, but with much simpler strategies for long periods of time in practical use.