一種改進(jìn)遺傳算法的自動(dòng)組卷系統(tǒng)優(yōu)化研究

劉雅莉

摘要：

基于改進(jìn)的傳統(tǒng)遺傳算法完成了一種自動(dòng)組卷系統(tǒng)的設(shè)計(jì)，使用改進(jìn)遺傳算法構(gòu)建了一種包括試題編碼方法、選擇交叉算子、設(shè)置變異等環(huán)節(jié)在內(nèi)的智能組卷策略，對(duì)組卷過(guò)程的適應(yīng)度函數(shù)通過(guò)加權(quán)目標(biāo)函數(shù)的建立完成優(yōu)化處理，進(jìn)而實(shí)現(xiàn)良好的適應(yīng)度的獲取，選擇操作環(huán)節(jié)通過(guò)結(jié)合運(yùn)用保優(yōu)策略和輪盤賭方法得到了進(jìn)一步優(yōu)化，在實(shí)現(xiàn)快速成功組卷的同時(shí)提高了組卷質(zhì)量。根據(jù)系統(tǒng)的仿真實(shí)驗(yàn)證實(shí)了自動(dòng)組卷系統(tǒng)的可行性。

關(guān)鍵詞：

遺傳算法; 組卷系統(tǒng); 優(yōu)化分析

中圖分類號(hào)： TP 291

文獻(xiàn)標(biāo)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