文章摘要
游 尧,林培群.基于智能优化算法的动态路径诱导方法研究进展[J].交通运输研究,2015,1(1):20-26.
基于智能优化算法的动态路径诱导方法研究进展
New Trends of Dynamic Route Guidance Methods Based on Intelligent Optimization Algorithms
  
DOI:
中文关键词: 动态路径诱导方法  研究进展  智能优化算法  蚁群算法  遗传算法
英文关键词: dynamic route guidance methods  research progress  intelligent optimization algorithms  ant colony optimization  genetic algorithm
基金项目:
作者单位
游 尧 华南理工大学 土木与交通学院 
林培群 华南理工大学 土木与交通学院 
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中文摘要:
      采用综述的方法对当前动态路径诱导方法中一些有代表性的智能优化算法进行了深刻的探讨与总结, 为未来进行深入而广泛的智能交通系统研究及应用奠定基础。主要从算法特性、改进效果、性能评价等方面详细讨论了智能优化算法在动态路径诱导系统中的常见改进机制及其效果,给出了这些优化算法的基本思想、优缺点及其应用局限性;并对智能优化算法性能评价方法的研究现状进行了详细的分析与总结,为建模人员和研究人员对智能交通系统中动态路径诱导方法的选择和研究提供支持;最后结合算法应用分析成果,展望了智能优化算法在动态路径诱导系统中的应用发展前景和智能交通系统中进一步研究未来动态路径诱导算法的重要研究方向。
英文摘要:
      Some representative intelligent optimization algorithms in the dynamic route guidance methods were discussed and summed up by the review method, which laid a foundation for the future research in the intelligent transportation system deeply and widely. The improvement mechanism and the application results of the intelligent optimization algorithm are analyzed from the view of the algorithm characteristics, improvement effect, performance evaluation, etc. And the basic idea, advantages, disadvantages and limitations of these algorithms were given. Besides, the research status of evaluation methods of the intelligent optimization algorithm performance was analyzed, which helped engineers and researchers to select the most suitable variability modeling techniques. Finally, combining with the analysis results of algorithms application, the application prospect and some important research directions in the future further research of the intelligent optimization algorithms in intelligent transportation system were forecast.
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