Int J Performability Eng ›› 2023, Vol. 19 ›› Issue (7): 481-490.doi: 10.23940/ijpe.23.07.p7.481490

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Multi-Objective Optimization of Cancer Treatment Using the Multi-Objective Grey Wolf Optimizer (MOGWO)

Linkai Chen*, Honghui Fan, and Hongjin Zhu   

  1. School of Computer and Engineering, Jiangsu University of Technology, Changzhou, China
  • Contact: * E-mail address:

Abstract: The use of mathematical modeling to study biological phenomena is one of the best methods available for studying these phenomena. The development of mathematical models for simulating, controlling, and predicting phenomena has always been significant. The application of mathematical models in optimization is one of the advantages of using them. In the context of cancer treatment, the goal is to reduce the concentration of cancer cells during the treatment period through optimal control. An important issue that was not considered in previous studies was the concentration of the active drug, which had a significant influence on the clinical health of the patients. The aim of the current study was to establish a protocol for optimal drug administration by minimizing the concentration of cancer cells and the concentration of the drug. The multi-objective grey wolf optimizer (MOGWO) algorithm was used for the first time to solve this multi-objective problem and the results were compared to those obtained with the NSGA-II algorithm.

Key words: cancer, optimization, gray wolf algorithm, the concentration of cancer cells