Chen Liting, Chen Shengqun, Zheng Jing, Gao Jianqing
College of Electronics and Information Science, Fujian Jiangxia University, Fuzhou 350108, China.
Research Institute for Data Analysis and Intelligent Decision-Making, Fujian Jiangxia University, Fuzhou 350108, China.
J Saf Sci Resil. 2022 Dec;3(4):330-339. doi: 10.1016/j.jnlssr.2022.08.001. Epub 2022 Aug 23.
To solve the problem of volunteer dispatch during the Coronavirus Disease 2019 (COVID-19) epidemic, a many-to-many two-sided matching volunteer dispatch method based on an improved predator-search algorithm is proposed. First, different evaluation index sets for volunteers and rescue tasks were developed, and weightings were determined using the analytic hierarchy process. Subsequently, the actual and expected values of the different indicators of the two parties were determined, and the triangular fuzzy number was used to calculate the satisfaction of the two parties. Based on this number, we used a linear weighting method to calculate the combined satisfaction and build a many-to-many two-sided matching model according to the demands of both parties. Subsequently, an improved predator-search algorithm was used to solve the model. Finally, taking the recruitment of volunteers for pneumonia epidemic prevention and control in Chun'an County as an example, the method proposed in our study was verified. A comparison and analysis of the results further demonstrated the feasibility and advantages of this method.
为解决新型冠状病毒肺炎(COVID-19)疫情期间的志愿者调度问题,提出了一种基于改进捕食搜索算法的多对多双边匹配志愿者调度方法。首先,针对志愿者和救援任务制定了不同的评价指标集,并采用层次分析法确定权重。随后,确定双方不同指标的实际值和期望值,并用三角模糊数计算双方的满意度。基于该数值,采用线性加权法计算综合满意度,并根据双方需求建立多对多双边匹配模型。随后,使用改进的捕食搜索算法求解该模型。最后,以淳安县肺炎疫情防控志愿者招募为例,验证了本研究提出的方法。结果的对比分析进一步证明了该方法的可行性和优势。