Modified Particle Swarm Optimizer with Adaptive Dynamic Weights for Cancer Combinational Chemotherapy

摘要

Cancer combinational chemotherapy is a complex treatment process that requires balancing the administration of anti-cancer drug to reduce tumor size with the adverse toxic side effects caused by these drugs. Methods of computational optimization like Genetic Algorithm (GA) and Canonical Particle Swarm Optimization (CPSO) have been used to strike the right balance. The purpose of this paper is to study how an alternative optimization technique -Modified Particle Swarm Optimizer (MPSO) - can be used for finding optimal chemotherapeutic treatments in an efficient manner. Comparison of its performance with the other existing algorithms of MPSO has been shown.