Improved Particle Swarm Optimization for the Mutual Inductance of an Implantable Biomedical Application
Marouani Houcine, Amin Sallem, Mondher Chaoui, Masmoudi Nouri · 2019
Particle Swarm Optimization (PSO) and Differential Evolution (DE) are two dominant metaheuristic optimization techniques with different special features. These specialties are combined together in an improved particle swarm optimization (DPSO) algorithm is estimated. The proposed idea consists of incorporating the concept of the DE algorithm when updating velocity equation of the PSO algorithm in sort to guarantee the global optimal. Also, the objective is to bias the solution, the difference between the selected randomly and the target particle, with an adjust parameter. The improved algorithm is simulated on several test functions and compared between three references metaheuristics and one variant most used in the literature. Then, DPSO has been used to optimize the mutual inductance of an implantable biomedical problem.