Performance Comparison of Metaheuristic Algorithms on FOPID-Controlled Anti-Cancer Drug Delivery System

Chemotherapy is one of the most effective and preferred treatment methods in cancer treatment. It is essential to finely adjust chemotherapy drug doses for the patient's survival and comfort in terms of side effects during the treatment process. In this study, a well-known anti-cancer drug scheduling patient model was used. This patient model was controlled by an optimized fractional order proportional-integral-derivative (FOPID) controller. In the optimization process five different swarm-based metaheuristic algorithms such as AHA, GWO, PSO, SSA, and WOA were used. To compare their performances, each algorithm was run independently 30 times and statistical data was collected. As a result of the simulation studies, the GWO-based optimal FOPID (GWO-FOPID) and PSO-based optimal FOPID (PSO-FOPID) controllers outperformed with the final number of cancer cells (CCs) of 35.253 and 35.255, respectively. Moreover, the highest performance index of 24.07 was achieved for these controllers.