Multi-objective Optimisation of Cancer Chemotherapy using Smart PSO with Decomposition

Al Moubayed, N; Petrovski, A; McCall, J

Abstract

The paper presents a novel approach to optimising cancer chemotherapy with respect to conflicting treatment objectives aimed at reducing the number of cancerous cells and at limiting the amounts of anti-cancer drugs used. The approach is based on the Particle Swarm Optimisation (PSO) algorithm that decomposes a multi-objective optimisation problem into several scalar aggregation problems, thereby reducing its complexity and enabling an effective application of Computational Intelligence techniques. The novelty of the algorithm is in providing particles in the swarm with information from a set of defined neighbours and leaders that assists in finding versatile chemotherapeutic treatments.

Citation

Al Moubayed, N., Petrovski, A., & McCall, J. (2011). Multi-objective Optimisation of Cancer Chemotherapy using Smart PSO with Decomposition. . https://doi.org/10.1109/smdcm.2011.5949264

• Conference Name: 2011 IEEE Symposium on Computational Intelligence in Multicriteria Decision-Making (MDCM)
• Conference Location: Paris, France
• Start Date: Apr 11, 2011
• End Date: Apr 15, 2011
• Online Publication Date: Jul 11, 2011
• Publication Date: 2011
• Deposit Date: Jan 26, 2016
• Publisher: Institute of Electrical and Electronics Engineers
• Pages: 81 - 88
• ISBN: 978-1-61284-068-0
• DOI: https://doi.org/10.1109/smdcm.2011.5949264
• Public URL: https://durham-repository.worktribe.com/output/1151166