基于改进差分进化的智能综合评分法

王荣笙; 王晓刚; 龙艺璇; 吕宜生; 袁志明

doi:10.11959/j.issn.2096-6652.202506

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基于改进差分进化的智能综合评分法

学术论文 | 更新时间：2025-06-10

- 基于改进差分进化的智能综合评分法
- An intelligent comprehensive scoring approach based on improved differential evolution algorithm
- 智能科学与技术学报 2025年7卷第1期页码：64-76
- 作者机构：
  
  1.中国铁道科学研究院集团有限公司科学技术信息研究所，北京 100081
  2.中国科学院自动化研究所复杂系统管理与控制国家重点实验室，北京 100190
  3.中国铁道科学研究院集团有限公司通信信号研究所，北京 100081
  4.高速铁路与城轨交通系统技术国家工程研究中心高速铁路行车调度实验室，北京 100081
- 作者简介：
  
  [ "王荣笙（1994- ），男，中国铁道科学研究院集团有限公司助理研究员，主要研究方向为进化计算、综合评价方法、人工智能、铁路运输等。" ]
  [ "王晓刚（1976- ），男，博士，中国铁道科学研究院集团有限公司研究员，主要研究方向为科研管理、知识产权管理。" ]
  [ "龙艺璇（1994- ），女，博士，中国铁道科学研究院集团有限公司高级工程师，主要研究方向为科技评价、科技情报分析、科学计量。" ]
  [ "吕宜生（1983- ），男，博士，中国科学院自动化研究所研究员，主要研究方向为人工智能、智能网联驾驶、平行交通管理与控制系统。" ]
  [ "袁志明（1980- ），男，博士，中国铁道科学研究院集团有限公司研究员，主要研究方向为铁路调度指挥、铁路信号控制。" ]
- 基金信息：
  
  中国铁道科学研究院集团有限公司科研开发基金项目(2024YJ030);北京市自然科学基金项目(4254110);中国国家铁路集团有限公司科技研究开发计划项目(Q2024Z009)
- DOI：10.11959/j.issn.2096-6652.202506
  中图分类号： TP182;N945.16
- 收稿：2024-11-11，
  
  修回：2025-01-25，
  
  纸质出版：2025-03-15
- 稿件说明：
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王荣笙,王晓刚,龙艺璇等.基于改进差分进化的智能综合评分法[J].智能科学与技术学报,2025,07(01):64-76.

WANG Rongsheng,WANG Xiaogang,LONG Yixuan,et al.An intelligent comprehensive scoring approach based on improved differential evolution algorithm[J].Chinese Journal of Intelligent Science and Technology,2025,07(01):64-76.
王荣笙,王晓刚,龙艺璇等.基于改进差分进化的智能综合评分法[J].智能科学与技术学报,2025,07(01):64-76. DOI： 10.11959/j.issn.2096-6652.202506.

WANG Rongsheng,WANG Xiaogang,LONG Yixuan,et al.An intelligent comprehensive scoring approach based on improved differential evolution algorithm[J].Chinese Journal of Intelligent Science and Technology,2025,07(01):64-76. DOI： 10.11959/j.issn.2096-6652.202506.

摘要

针对综合评价问题中的异常评分导致的综合评分结果有失公允问题，提出基于改进差分进化的智能综合评分法，通过剔除异常评分提升综合评分结果的公平性。首先，从异常评分产生的根本原因出发，定义综合评价问题的公平性指标及目标函数，分析问题约束条件和异常评分判定条件。其次，提出基于改进差分进化的智能综合评分法，即在传统差分进化算法的框架上做出以下3点改进：提出基于评分值权数的实数编解码方式；采用比重法将评分值权数等式约束写入目标函数，将综合评价问题转化为无约束优化问题，提升算法求解效率；以公平性指标为基础，设计评分值权数优化问题知识，采用启发式种群初始化方法提升算法前期收敛速度和评分值权数结果的求解质量。最后，算例结果表明，所提出的智能综合评分法能自动判定权数较小的评分值为异常评分并予以剔除，最终在13 s内给出公平性更高的综合评分结果，有效提升了综合评分结果的公平公正性与科学合理性。

Abstract

In response to the issue of biased comprehensive evaluation results caused by anomalous ratings in comprehensive evaluation problems

an intelligent comprehensive scoring approach based on improved differential evolution algorithm had been proposed

which enhanced the fairness of comprehensive evaluation results by eliminating anomalous ratings. Firstly

considering the causes of abnormal scores

the fairness index and objective function were defined for the comprehensive evaluation problem. The constraint and the criterion of abnormal scores were also analyzed. Secondly

an intelligent comprehensive scoring approach had been proposed based on improved differential evolution algorithm

which introduced the following three improvements to the traditional differential evolution algorithm framework: a real encoding and decoding method was developed based on the score weights. The weighting method was used to write the constraints of the score weights into the objective function. As a result

the comprehensive evaluation problem was transformed into an unconstrained optimization problem to improve efficiency. The problem-specific knowledge of score weights was designed based on the fairness index. A heuristic population initialization method was employed to speed up the algorithm convergence in the early stage and the solution quality of the score weights. Finally

the case study results had demonstrated that the proposed intelligent comprehensive scoring approach could automatically identify ratings with smaller weights as anomalous and eliminate them

ultimately providing a more fair comprehensive evaluation result within 13 seconds

effectively improving the fairness

impartiality

and scientific rationality of the comprehensive evaluation results.

关键词

Keywords

references

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