Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.11861/7570
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Tse, Sui-Man | en_US |
dc.contributor.author | Liang, Yong | en_US |
dc.contributor.author | Prof. LEUNG Kwong Sak | en_US |
dc.contributor.author | Lee, Kin-Hong | en_US |
dc.contributor.author | Mok, Tony Shu-Kam | en_US |
dc.date.accessioned | 2023-03-24T02:22:41Z | - |
dc.date.available | 2023-03-24T02:22:41Z | - |
dc.date.issued | 2007 | - |
dc.identifier.citation | IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 2007, vol. 37 (1) , pp. 84 - 91 | en_US |
dc.identifier.issn | 10834419 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.11861/7570 | - |
dc.description.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. © 2007 IEEE. | en_US |
dc.language.iso | en | en_US |
dc.relation.ispartof | IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics | en_US |
dc.title | A memetic algorithm for multiple-drug cancer chemotherapy schedule optimization | en_US |
dc.type | Peer Reviewed Journal Article | en_US |
dc.identifier.doi | 10.1109/TSMCB.2006.883265 | - |
item.fulltext | No Fulltext | - |
crisitem.author.dept | Department of Applied Data Science | - |
Appears in Collections: | Applied Data Science - Publication |
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