Multi-Objective Optimization of Ionization Chamber Structure Based on Genetic Algorithm

Ionization chambers play a crucial role in large-scale radiation imaging systems. However, the response time of conventional parallel-plate ionization chambers is too long to meet the requirements for rapid detection. To address this issue, a grid detector was previously proposed, significantly reducing detector response time. However, optimizing the structure of this type of detector is challenging due to its numerous parameters. In particular, the key parameters—response time and output current—are inherently conflicting, making it inefficient to rely on enumeration or empirical methods for structural optimization. To overcome this limitation, this paper introduces a multi-objective optimization approach based on the NSGA-II algorithm to optimize the response time and output current of grid ionization chambers under given constraints. The results demonstrate that the proposed method efficiently provides a design solution that meets practical requirements, offering a novel approach to the structural optimization of ionization chambers.