一種改進遺傳算法的自動組卷系統優化研究

劉雅莉

摘要：

基于改進的傳統遺傳算法完成了一種自動組卷系統的設計，使用改進遺傳算法構建了一種包括試題編碼方法、選擇交叉算子、設置變異等環節在內的智能組卷策略，對組卷過程的適應度函數通過加權目標函數的建立完成優化處理，進而實現良好的適應度的獲取，選擇操作環節通過結合運用保優策略和輪盤賭方法得到了進一步優化，在實現快速成功組卷的同時提高了組卷質量。根據系統的仿真實驗證實了自動組卷系統的可行性。

關鍵詞：

遺傳算法; 組卷系統; 優化分析

中圖分類號： TP 291

文獻標志碼： A

Research on Optimization of Automatic Test Paper Generation

System Based on Improved Genetic Algorithm

LIU Yali

（Faculty of Economics and Management， Shangluo University， Shangluo， Shanxi 726000， China）

Abstract：

This paper has completed the design of an automatic test paper generation system based on improved traditional genetic algorithm， and used the improved genetic algorithm to construct an intelligent test paper generation strategy that includes test coding methods， selection of crossover operators， and setting of mutations. The fitness function of the test paper composition process is optimized through the establishment of a weighted objective function， thereby achieving a good fitness. The selection operation is further optimized by combining the use of a premium strategy and a roulette method， achieving rapid success. At the same time， the quality of the test paper is improved. And the simulation experiments verify the practicability of the test paper algorithm.

Key words：

genetic algorithm; volume grouping system; optimization analysis