This chapter mainly proposes an evolutionary algorithm and its first application to develop therapeutic strategies for Ecological Evolutionary Dynamics Systems (EEDS), obtaining the balance between tumor cells and immune cells by rationally arranging chemotherapeutic drugs and immune drugs. Firstly, an EEDS nonlinear kinetic model is constructed to describe the relationship between tumor cells, immune cells, dose, and drug concentration. Secondly, the N-Level Hierarchy Optimization (NLHO) algorithm is designed and compared with 5 algorithms on 20 benchmark functions, which proves the feasibility and effectiveness of NLHO. Finally, we apply NLHO into EEDS to give a dynamic adaptive optimal control policy, and develop therapeutic strategies to reduce tumor cells, while minimizing the harm of chemotherapy drugs and immune drugs to the human body. The experimental results prove the validity of the research method.
N-Level Hierarchy-Based Optimal Control to Develop Therapeutic Strategies for Ecological Evolutionary Dynamics Systems
Adaptive Dynamic Programming ; Chapter : 5 ; 77-92
2023-09-13
16 pages
Article/Chapter (Book)
Electronic Resource
English
A New Evolutionary Algorithm based on Chromosome Hierarchy Network
British Library Online Contents | 2008
|Evolutionary Dynamics Optimal Research-Oriented Tumor Immunity Architecture
Springer Verlag | 2023
|Tif Interactive workshops to develop new strategies
British Library Online Contents | 2003
Using Reinforcement Learning and Simulation to Develop Autonomous Vehicle Control Strategies
SAE Technical Papers | 2020
|