计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2013年
14期
227-230,246
,共5页
朱婧%戴青云%王美林%王森洪
硃婧%戴青雲%王美林%王森洪
주청%대청운%왕미림%왕삼홍
遗传算法%工程训练%智能组卷%整数编码%自适应%最优个体保存机制
遺傳算法%工程訓練%智能組捲%整數編碼%自適應%最優箇體保存機製
유전산법%공정훈련%지능조권%정수편마%자괄응%최우개체보존궤제
genetic algorithm%engineering training%intelligent test paper composition%integer coding%adaptive%best individual saving mechanisms
在工程训练中心车间信息化实现的基础上,针对工程训练管理系统中考试模块现有组卷方式所带来的抽重复题、组卷效率低下等问题,以满足在线考试的实时性要求。为此,给出一种改进的遗传算法,采用分段整数编码,改进初始种群的产生方法,有效提高了算法的收敛速度,并自适应调整遗传算子,在进化过程中增加去重题策略及最优个体保存机制,维护了种群多样性,保证了运算结果的质量。实验结果表明,该算法不但解决了系统组卷原有的问题,在迭代次数、运行时间和组卷精确度上均明显优于随机组卷法和简单遗传算法。
在工程訓練中心車間信息化實現的基礎上,針對工程訓練管理繫統中攷試模塊現有組捲方式所帶來的抽重複題、組捲效率低下等問題,以滿足在線攷試的實時性要求。為此,給齣一種改進的遺傳算法,採用分段整數編碼,改進初始種群的產生方法,有效提高瞭算法的收斂速度,併自適應調整遺傳算子,在進化過程中增加去重題策略及最優箇體保存機製,維護瞭種群多樣性,保證瞭運算結果的質量。實驗結果錶明,該算法不但解決瞭繫統組捲原有的問題,在迭代次數、運行時間和組捲精確度上均明顯優于隨機組捲法和簡單遺傳算法。
재공정훈련중심차간신식화실현적기출상,침대공정훈련관리계통중고시모괴현유조권방식소대래적추중복제、조권효솔저하등문제,이만족재선고시적실시성요구。위차,급출일충개진적유전산법,채용분단정수편마,개진초시충군적산생방법,유효제고료산법적수렴속도,병자괄응조정유전산자,재진화과정중증가거중제책략급최우개체보존궤제,유호료충군다양성,보증료운산결과적질량。실험결과표명,해산법불단해결료계통조권원유적문제,재질대차수、운행시간화조권정학도상균명현우우수궤조권법화간단유전산법。
On the basis of realizing the information technology in the engineering training center workshop, the management system of examination module has a lot of problems, such as forming repeated questions and the low efficiency of paper con-structing, in order to solve those problems to meet the real-time requirements of the on-line exam, this paper presents an improved genetic algorithm. In this algorithm, it adopts the subsection integer coding, improves the generation methods of the initial popu-lation, which can effectively improve the convergence speed. It also uses the adjustment method of adaptive genetic operator, then removes the repeated questions and adds best individual save mechanism in the evolutionary process, which can both ensure the diversity of population and acquire high quality. The experimental results show that the algorithm can not only solve the problem of the examination module, but also show the advantages over randomized algorithms and simple genetic algorithm in iterative times, running times and accuracy of composition test paper.