摘要
针对高等学校资源优化配置与管理问题,在收集72所高校五年投入产出数据并进行绩效评价的基础上,以投入产出绩效作为资源配置目标,建立高校资源优化配置的两层结构模型.采用神经网络与遗传算法相结合,建立非线性适应值函数,以优化不同学校一级投入指标的投入比例.最后对配置结果进行风险分析,以评价配置的可行性,尽可能避免资源配置的不合理或损失出现.研究结果为高校资源配置突破传统模式提供了有效的管理方法.
According to resource optimization allocation and management problems of uni- versities, on the basis of the collection on input and output data and performance evaluation of 72 universities in 5 years, input and output performance as the goal of resource allocation, a two-layer resource optimization allocation model is established. Combining neural network and genetic algorithm, in order to optimize the input ratio of the first level of the different schools, we establish a nonlinear adaptive value function. Finally, analysis is conducted on the results of allocation to evaluate the feasibility of the allocation and avoid an unreasonable allocation of resources and avoid loss as far as possible. The results of this paper provide an effective way on management to break through the traditional allocation mode of resource allocation in universities.
作者
廖芹
张莹
LIAO Qin;ZHANG Ying(Department of Mathematics, South China University of Technology, Guangzhou 510640, China)
出处
《数学的实践与认识》
北大核心
2017年第21期52-59,共8页
Mathematics in Practice and Theory
关键词
资源配置
神经网络
遗传优化
风险预测
resource allocation
neural network
genetic optimization
risk prediction
