用于求解井下最短逃生路径问题的离散萤火虫算法

张雪英, 李智勇, 李凤莲, 陈桂军

张雪英,李智勇,李凤莲,等.用于求解井下最短逃生路径问题的离散萤火虫算法[J].工矿自动化,2016,42(12):30-35.. DOI: 10.13272/j.issn.1671-251x.2016.12.007
引用本文: 张雪英,李智勇,李凤莲,等.用于求解井下最短逃生路径问题的离散萤火虫算法[J].工矿自动化,2016,42(12):30-35.. DOI: 10.13272/j.issn.1671-251x.2016.12.007
ZHANG Xueying, LI Zhiyong, LI Fenglian, CHEN Guiju. A discrete firefly algorithm for solving the shortest escape path problem in-underground coal mine[J]. Journal of Mine Automation, 2016, 42(12): 30-35. DOI: 10.13272/j.issn.1671-251x.2016.12.007
Citation: ZHANG Xueying, LI Zhiyong, LI Fenglian, CHEN Guiju. A discrete firefly algorithm for solving the shortest escape path problem in-underground coal mine[J]. Journal of Mine Automation, 2016, 42(12): 30-35. DOI: 10.13272/j.issn.1671-251x.2016.12.007

用于求解井下最短逃生路径问题的离散萤火虫算法

基金项目: 

山西省科技重大专项项目(20121101004)

山西省国际科技合作项目(2015081007)

山西省科技攻关资助项目(20130321004-01)

详细信息
  • 中图分类号: TD773

A discrete firefly algorithm for solving the shortest escape path problem in-underground coal mine

  • 摘要: 针对煤矿井下避灾路线最短路径求解问题,提出了一种新的离散萤火虫算法。该算法通过采用转移概率方法初始化萤火虫个体,并提出一种新的有效编码和解码方式,重新定义萤火虫的空间距离、最大荧光亮度和相对荧光亮度等,使得萤火虫个体的状态可表示为一条从起点到目标点的有效路径。为增加解的多样性及防止计算结果陷入局部最优解,以一定概率对萤火虫代表的路径执行扰动操作,经过多次迭代计算后,可得到所要求解的最短路径。实验结果表明,该算法在种群规模较小、迭代次数较少的情况下可以收敛到最优解,具有较强的收敛性和灵活性,可用于求解任何实际的最短路径问题。
    Abstract: A new discrete firefly algorithm was proposed to solve the shortest escape path problem in underground coal mine. Firstly, the firefly individual was initialized using transfer probability method. And then, a new efficient encoding and decoding method was proposed to redefine space distance, the maximum fluorescence intensity and fluorescence relative brightness of the firefly. So the firefly individual state can be expressed as an effective path from the starting point to the target point. In order to increase the diversity of solutions and to prevent the solutions falling into the local optimum, disturbed operation was carried out to the represented path of the firefly by a certain probability. After several iterations, the shortest path of the solution can be obtained. The experimental results show that the proposed algorithm can converge to the optimal solution with the smaller population size and less iterations than the other algorithms, and has strong convergence and flexibility, which can be used to solve any problem of the shortest path.
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出版历程
  • 刊出日期:  2016-12-09

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