Optimal vaccination schedules using simulated annealing.
CONCLUSIONS
Since few years the problem of finding optimal solutions for drug or vaccine protocols have been tackled using system biology modeling. These approaches are usually computationally expensive. Our previous experiences in optimizing vaccine or drug protocols using genetic algorithms required the use of a high performance computing infrastructure for a couple of days. In the present article we show that by an appropriate use of a different optimization algorithm, the simulated annealing, we have been able to downsize the computational effort by a factor 10(2). The new algorithm requires computational effort that can be achieved by current generation personal computers.


BACKGROUND
Software and additional data can be found at http://www.immunomics.eu/SA/
Department of Mathematics and Computer Science, University of Catania, University of Catania, Catania, Italy.
Marzio
M
Pennisi
Roberto
R
Catanuto
Francesco
F
Pappalardo
Santo
S
Motta
D003140:Communicable Disease Control / Q000379:methods*; D003198:Computer Simulation; D020000:Decision Support Systems, Clinical; D004334:Drug Administration Schedule; D004360:Drug Therapy, Computer-Assisted / Q000379:methods*; D006801:Humans; D008954:Models, Biological; D014611:Vaccination / Q000379:methods*; D014612:Vaccines / Q000008:administration & dosage*
D014612:Vaccines