title: A memetic algorithm for multiple-drug cancer chemotherapy schedule optimization.
abstract: This correspondence introduces a multidrug cancer chemotherapy model to simulate the possible response of the tumor cells under drug administration. We formulate the model as an optimal control problem. The algorithm in this correspondence optimizes the multidrug cancer chemotherapy schedule. The objective is to minimize the tumor size under a set of constraints. We combine the adaptive elitist genetic algorithm with a local search algorithm called iterative dynamic programming (IDP) to form a new memetic algorithm (MA-IDP) for solving the problem. MA-IDP has been shown to be very efficient in solving the multidrug scheduling optimization problem.
authors.forename: Sui-Man
authors.initials: SM
authors.lastname: Tse
authors.forename: Yong
authors.initials: Y
authors.lastname: Liang
authors.forename: Kwong-Sak
authors.initials: KS
authors.lastname: Leung
authors.forename: Kin-Hong
authors.initials: KH
authors.lastname: Lee
authors.forename: Tony Shu-kam
authors.initials: TS
authors.lastname: Mok
mesh_terms: D000465:Algorithms; D000971:Antineoplastic Combined Chemotherapy Protocols / Q000008:administration & dosage* / Q000493:pharmacokinetics; D001185:Artificial Intelligence; D032701:Biomimetics / Q000379:methods*; D003198:Computer Simulation; D004334:Drug Administration Schedule; D004360:Drug Therapy, Computer-Assisted / Q000379:methods*; D006801:Humans; D008954:Models, Biological; D009369:Neoplasms / Q000188:drug therapy* / Q000378:metabolism; D012984:Software; D013598:Systems Theory