Optimal Control for Cancer Chemotherapy using Genetic Algorithm

Chemotherapy is known as a useful method to reduce or eliminate the several residual diseases such as various types of cancers. In this way, the objective is to maximize the likelihood that the cancer will be eliminated. Classic optimization methods to determine the chemotherapy regime has been used for various types of cancers for many years ago. These methods usually use deterministic model for cancer and tumor growth provided chemotherapy protect. In recent year a new stochastic model of chemotherapy with cell sensitive to drugs include normal system growth functions has been proposed. This is cause to repaying new visits to chemotherapy and conventional treatment. An important result of this scheme is broken equivalent drug scenario treatment regime. In this paper, we solve an optimization problem using global optimization algorithm, GA (Genetic Algorithm) and compare this results with the previous optimization scheme, which has been referred in [4]. Non-equivalent drug delivery, which given from GA optimization has better effect on cure probability than equivalent drugs.