基于微粒群算法的组织评估优化方法及实例  

Optimizing Method and Real Case of Organization Evaluation Based on Particle Swarm Optimization

作　　者：徐海宁[1] 陈其晖[1] 

机构地区：[1]同济大学现代远程教育研究所,上海200092

出　　处：《计算机工程》2008年第11期179-180,196,共3页Computer Engineering

基　　金：国家自然科学基金资助重点项目(70531020);上海市教育科学基金资助重点项目(A0401);教育部人文社会科学研究青年基金资助项目(05JC88053)

摘　　要：组织评估的关键因素是合理地确定各项指标的权重。该文将微粒群算法应用于评估指标权重的寻优中,以专家组对初始评估模型进行修正的结果作为评估寻优的参考基准,给出一种基于该算法的权重优化解决方案。针对网大中国大学排行榜指标体系进行优化,验证了该算法的有效性。The key factor of performance evaluation is how to confirm the weighing of evaluation in a reasonable way. Particle Swarm Optimization （PSO） is applied to optimize the process of evaluation. Result of expert team＇s advice on correcting the original evaluation model is taken as reference benchmark of optimizing. A feasible solution based on this algorithm is advanced to optimize the evaluation weighing, and it is applied to the evaluation index system of NETBIG＇s Chinese University Rankings, and the validity is proved by the example.

关 键 词：评估 权重优化 群体智能 微粒群算法 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]