摘要:近幾年智能優(yōu)化算法倍受人們關(guān)注，并在諸多領(lǐng)域取得了成功。組卷問(wèn)題是一個(gè)在一定約束條件下的多目標(biāo)參數(shù)優(yōu)化問(wèn)題，傳統(tǒng)的組卷算法具有組卷速度慢、成功率較低、試卷質(zhì)量不高等缺點(diǎn)。隨著計(jì)算機(jī)輔助教學(xué)和人工智能的發(fā)展,大型題庫(kù)系統(tǒng)中，能決定組卷的質(zhì)量和效率的組卷算法逐漸被眾多專(zhuān)家所關(guān)注。

　　　本論文根據(jù)應(yīng)用型本科院校《自動(dòng)控制理論》課程特點(diǎn)，建立了試題庫(kù)，并通過(guò)對(duì)學(xué)生調(diào)查研究對(duì)試題屬性進(jìn)行了合理賦值。采用權(quán)重系數(shù)法將多目標(biāo)優(yōu)化問(wèn)題轉(zhuǎn)化為單目標(biāo)優(yōu)化問(wèn)題，建立了目標(biāo)函數(shù)和數(shù)學(xué)模型。針對(duì)單純遺傳算法存在許多缺點(diǎn)如早熟收斂、局部搜索能力不強(qiáng)等，本文編程實(shí)現(xiàn)了一種基于粒子群算法的改進(jìn)遺傳算法并將其應(yīng)用于智能組卷中，通過(guò)設(shè)置不同的參數(shù)在MATLAB平臺(tái)上進(jìn)行仿真實(shí)驗(yàn)。仿真實(shí)驗(yàn)的結(jié)果表明，改進(jìn)遺傳算法應(yīng)用于《自動(dòng)控制理論》智能組卷是合理可行的，可以有效節(jié)省教學(xué)資源，提高工作效率。

關(guān)鍵詞 智能優(yōu)化；自動(dòng)控制理論；數(shù)學(xué)模型；遺傳算法；早熟收斂

Abstract:In recent years, much attention is attached on intelligent optimization algorithms. They have been used successfully in many fields. Testing paper is a certain constraints under the multi-objective parameter optimization problem, the shortcomings of traditional algorithmic of testing paper are so obvious. The rate is very low and the quality of the paper is so poor. With the development of computer-assisted instruction and artificial intelligence, the algorithms that can determine the quality and efficiency of testing paper gradually attract the attention of many experts in large bank system.

　　　 The test database focusing on the characteristics of Automatic Control Theory course was established, and questions were reasonably assigned based on the research to the students in my thesis. The multi-objective optimization problems are turned into a single objective optimization problem by using weight coefficient method, the objective function and mathematical model are established meanwhile. A new algorithm that can solve the shortcomings of traditional genetic algorithm based on particle swarm optimization algorithm was used in this paper. For example, premature convergence and the local search ability is poor. The improved algorithm is applied in intelligent test, and it is validated by the simulation of MATLAB with changing the parameters. Simulation results show that, the new algorithm is feasible when used in testing paper. It can save the teaching resources and improve the work efficiency.

Keywords  Intelligent Optimization  Automatic Control Theory  Mathematical Model Genetic Algorithm  Premature Convergence