蚁群混合遗传算法的研究及应用

摘要/Abstract

摘要：

为解决组卷过程中在一定约束条件下存在的多目标优化问题,结合蚁群算法和遗传算法各自的优点和它们融合的基础,提出了一种蚁群算法融合到遗传算法的策略:在组卷的前阶段利用遗传算法群体性全局搜索能力,快速形成初始解,在满足终止遗传算法的条件后,将遗传算法调度的较优解转化为蚁群算法所需要的初期信息素,然后利用蚁群算法所具有的正反馈、高效等特点快速形成试卷最优解。实践结果证明此算法改善了试卷的质量以及系统的运行效率,生成的试卷符合要求,达到预期的结果。

关键词: 蚁群算法, 遗传算法, 混合算法, 组卷问题

Abstract:

In order to solve the problem of multi-objective optimization in test paper generation under some restricted conditions,this paper proposes fusing an ant colony algorithm into the genetic algorithm on the basis of the advantages of the ant colony algorithm and genetic algorithm and the foundation for their fusion:using the global searching capability of the genetic algorithm at the early stage of test paper generation,transforming the optimal solution scheduled by the genetic algorithm into initial pheromone the ant colony needs,and then quickly forming optimal solution to the test paper by taking advantage of the fact that the ant colony algorithm has the positive and negative feedback and the characteristic of high efficiency.Application shows that this algorithm improves the quality of the test and efficiency of the systems and the generated paper meets the requirement with desired effect achieved.

Key words: ant colony algorithms;genetic algorithms;hybrid algorithms;test paper generation

中图分类号:

TP301.6

柏建普, 吴强. 蚁群混合遗传算法的研究及应用[J]. , 2011, 24(4): 20-.

BAI Jian-Pu, WU Qiang. Research on and Application of Ant Colony Algorithms Hybrid Genetic Algorithms[J]. , 2011, 24(4): 20-.

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