An intelligent comprehensive scoring approach based on improved differential evolution algorithm

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.