Nanobiosensing from an In Vivo Multi-objective Optimization Perspective

In our study, due to the inefficiency of conventional medical imaging techniques for early tumor detection, we use an external magnetic field to guide nanoswimmers in high-risk tissue region to move through the biological gradient field (BGF) induced by tumor tissue and search for the tumor location. Since a tumor can generate multiple BGFs, we propose a novel framework named in vivo multi-objective optimization by viewing the BGFs as optimizable objective functions. Furthermore, we propose two computing techniques based on the traditional particle swarm optimization to solve this in vivo computational problem. Some simulation experiments are carried out by comparing the proposed techniques to the traditional brute-force search. The results show that both of the proposed techniques perform better than the brute-force search method for nanobiosensing.