摘要
针对公共设施选址问题中因多目标约束条件造成的复杂空间搜索问题,提出了一种基于遗传算法的P-中值模型,以设施点与供应点间的分配关系作为基因序列,将出行时间消耗、建设投入成本、容量限制条件等因素构成目标函数,用于设施供需分配过程中的优化求解。同时从初始种群构成方式和变异率两方面对遗传算法进行改进以提高求解准确性。实验将该模型运用于河南省省级医疗中心选址,并结合多种评价指标得出多样化的医疗中心布局方案,验证了模型的有效性和可行性。
In order to optimize the complex spatial search process caused by multi-objective constraint condition in locationallocation problem for public facilities, the p-median model based on genetic algorithm is proposed in this paper in the site allocation process. The distribution relationship between the facility and the supply point makes up the gene sequences while the travel time, capacity limits and other factors constitute the objective function. Optimized population initializing strategy and dynamic mutation rate are also adopted to further enhance the solving accuracy. This model has been tested in Henan to give diverse healthcare centers allocation results for different requirements, which validates the effectiveness and applicability of the proposed model.
出处
《计算机工程与应用》
CSCD
北大核心
2016年第6期13-18,25,共7页
Computer Engineering and Applications
基金
教育部博士点基金(No.20130141120075)
关键词
P-中值模型
遗传算法
设施选址
医疗中心
P-median model
genetic algorithm
facility location
healthcare center
