Research on Computational Intelligence in Medical Resource Allocation Based on Mass Customization
Yang Xu (Peking University, China)
Shuwen Liu (Peking University, China)
Binglu Wang (Peking University, China)
Abstract: In this era characterized by rapid improvements in the quality of living, people are eager to seek better medical services. However, the medical resource shortage threatens people's daily lives and has become an important factor causing dissatisfaction. Furthermore, as a sub-branch of artificial intelligence, computational intelligence is widely used to solve real-world problems like resource allocation. This paper proposes a medical resource allocation model based on mass customization, considering parameters such as doctors' professional level, patient preferences, and the medical station distribution. This model aims at optimizing and balancing the uneven distribution of medical resources by taking into account the patient requirements and medical costs. Moreover, a genetic algorithm is applied to improve the computational efficiency of the proposed method. The results show that the medical resource allocation model based on mass customization can lead to a higher profit. Suggestions are also discussed for sustainable development in medical service based on mass customization.
Keywords: allocation model, computational intelligence, mass customization, medical resources, willingness to pay