Abstract
Hospital inspection tasks include temperature measurement, disinfection, emergency treatment, etc. Inspection robots can assist people in carrying out autonomous inspections and reduce the pressure on hospital staff. In this paper, we focus on the task assignment of hospital inspection robots, i.e., assigning multiple tasks to different robots to achieve the highest level of task completion. For the task assignment model of the inspection robots, a multi-objective mathematical model of task assignment is established, considering the benefit, cost, and execution time of task assignment. For the optimization scheme, a hybrid algorithm of discrete differential evolution and particle swarm optimization (D-DEPSO) algorithm is designed, applying differential mutation operation to the population initialization process of the particle swarm optimization (PSO) algorithm to expand the diversity of the population and improve the optimization-seeking ability of the algorithm. For coordination among objectives, the adjustment method of objective weights is proposed so as to achieve balance among objectives. The experimental results show that the designed method can improve the utility of task assignment in the hospital inspection process and thus efficiently complete the hospital inspection tasks.
R. B. G. thanks Natural Science Fund of Shanxi Province (202203021211198).
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Zhang, C.M., Ma, X.Y., Zhai, B. (2024). Hybrid D-DEPSO for Multi-objective Task Assignment in Hospital Inspection. In: Xin, B., Kubota, N., Chen, K., Dong, F. (eds) Advanced Computational Intelligence and Intelligent Informatics. IWACIII 2023. Communications in Computer and Information Science, vol 1931. Springer, Singapore. https://doi.org/10.1007/978-981-99-7590-7_26
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