Hybrid population migration algorithm for parameters of pharmacokinetics

To overcome the weakness of poor accuracy of traditional methods in terms of optimization of pharmacokinetics parameters, this paper combines the Population Migration Algorithm(PMA)with the Hooke-Jeeves(HJ)algorithm and the order is to make them learn from others’strong points to offset one’s weaknesses, which not only improves the accuracy of the algorithm, but also speeds up the convergence velocity of the algorithm. Applying the Hybrid Population Migration Algorithm(HPMA)in the experiment on the optimization of two-compartment model’s parameters by extra-vascular administration can achieve a better effect than the traditional method of Feathering method(FM)and higher precision than the HJ or the PMA. Repeated experiments show that this algorithm has strong reliability and stability, and is a good approach for solving pharmacokinetic parameters.