Optimising Cancer Chemotherapy Using Particle Swarm Optimisation and Genetic Algorithms

Cancer chemotherapy is a complex treatment mode that requires balancing the benefits of treating tumours using anti-cancer drugs with the adverse toxic side-effects caused by these drugs. Some methods of computational optimisation, Genetic Algorithms in particular, have proven to be useful in helping to strike the right balance. The purpose of this paper is to study how an alternative optimisation method - Particle Swarm Optimisation - can be used to facilitate finding optimal chemotherapeutic treatments, and to compare its performance with that of Genetic Algorithms.

• Type: Conference
• Year: 2004
• Where: PPSN
• Authors: Andrei Petrovski, Bhavani Sudha, John A. W. McCall
• Keywords: Adverse Toxic Side-effects, Distributed And Parallel Computing, Genetic Algorithms, Particle Swarm Optimisation, PPSN 2004