Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.11861/7598
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, Shu-Kam Tony | en_US |
dc.date.accessioned | 2023-03-27T03:21:15Z | - |
dc.date.available | 2023-03-27T03:21:15Z | - |
dc.date.issued | 2005 | - |
dc.identifier.citation | 2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005. Proceedings, vol. 1, pp. 699 - 706 | en_US |
dc.identifier.isbn | 0780393635 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.11861/7598 | - |
dc.description.abstract | This paper proposes a new memetic algorithm (MA) to solve the Multi-drug chemotherapy optimization problem. The new MA combines GA with a local search algorithm called Iterative Dynamic Programming (IDP). A multi-drug chemotherapy model is introduced to simulate the possible response of the tumor cells under drugs administration. Optimization of the multiple chemotherapeutic agents' administration schedules is based on this tumor model. We formulate the optimization problem as an optimal control problem (OCP) with a set of dynamic equations. The objective is to design efficient schedules which minimize the tumor size under a set of constraints. Our new MA has been shown to be very efficient on solving our Multi-drug model. © 2005 IEEE. | en_US |
dc.language.iso | en | en_US |
dc.relation.ispartof | 2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005. Proceedings | en_US |
dc.title | Multi-drug cancer chemotherapy scheduling by a new memetic optimization algorithm | en_US |
dc.type | Conference Paper | en_US |
item.fulltext | No Fulltext | - |
crisitem.author.dept | Department of Applied Data Science | - |
Appears in Collections: | Applied Data Science - Publication |
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