2025/01/01 by Gao, Yuhao, Wecken, Lena, Lennerts, Kunibert +1
Engineering · Health Professions · Psychology · #600 | Technology (Applied Sciences)::620 | Engineering & #Advanced Manufacturing and Logistics Optimization #Facilities and Workplace Management #Healthcare Operations and Scheduling Optimization #allied operations #function scheme #genetic algorithm #hospital planning #quadratic assignment problem #transport effort
paper · doi:10.15488/19023
openalex publication_date 2025/01/01 · openalex created_date 2025/11/05 · openalex updated_date 2026/07/01
This study proposes a function scheme optimization method based on genetic algorithm, which aims to optimize the spatial layout within the hospital, reduce logistics and labour costs, and improve resource utilisation efficiency. Hospital layout planning is modelled as a quadratic assignment problem (QAP). In this framework, the object flow intensity of each functional area and between them is identified by constructing functional patterns and transformed into a flow-oriented ideal layout diagram. Elite selection, roulette selection, uniform crossover and mutation operations are used in the genetic algorithm, while parameters including elite ratio, crossover probability and mutation probability are set to achieve layout optimisation. The algorithm ensures the generation of feasible layouts through constraints such as room overlap and building boundary constraints, which also provides compactness ratio calculations to measure spatial dispersion and support layout optimisation. The case study results show that the proposed algorithm can efficiently generate layout solutions that conform to the functional pattern, which helps to reduce transport distances, reduce cross-contamination risks, and improve spatial utilisation and operational response speed of hospital resources.