A Soft Computing Approach for Optimal Drug Dosage Control using Chaotic Particle Swarm Optimization

The determination of an optimal drug dosage schedule is a critical issue in biomedical engineering, as inappropriate dosage may lead to severe side effects or insufficient therapeutic effects. Traditional optimization methods often face challenges when dealing with nonlinear and constrained pharmacokinetic models. This paper proposes a soft computing approach based on Chaotic Particle Swarm Optimization (CPSO) to achieve optimal drug dosage control. The incorporation of chaos theory into the particle swarm optimization framework enhances the exploration ability and prevents premature convergence, resulting in more accurate and robust solutions. The proposed method is applied to a pharmacokinetic model, where the objective function aims to maintain the drug concentration within the therapeutic window while minimizing adverse effects. Simulation results demonstrate that CPSO outperforms standard PSO and other evolutionary algorithms in terms of convergence speed, accuracy, and stability. The findings indicate that the proposed approach provides a promising framework for drug dosage optimization and can be extended to various biomedical applications.

کلیدواژه ها:

Soft Computing ، Chaotic Particle Swarm Optimization ، Optimal Control ، Dosage ، Biomedical Engineering ، Drug