系统仿真学报 ›› 2016, Vol. 28 ›› Issue (5): 1063-1069.

• 仿真建模理论与方法 • 上一篇    下一篇

改进布谷鸟算法在人群疏散多目标优化中的应用

董崇杰1, 刘毅2, 彭勇1   

  1. 1.东莞职业技术学院,东莞 523808;
    2.湖南省农机管理局,长沙 410011
  • 收稿日期:2015-04-30 修回日期:2015-07-03 发布日期:2020-07-03
  • 作者简介:董崇杰(1982-),男,山东菏泽,硕士,讲师,研究方向为数据库技术;刘毅(1984-), 男, 湖南长沙, 博士, 副研究员, 研究方向为智能计算。
  • 基金资助:
    广东省高等学校优秀青年教师培养计划项目(YQ2015232)

Improved Cuckoo Search Algorithm Applied to Multi-objective Optimization of Crowd Evacuation

Dong Chongjie1, Liu Yi2, Peng Yong1   

  1. 1.Dongguan Polytechnic, DongGuan 523808, China;
    2.Hunan Agricultural Machinery Management Bureau, Changsha 410011, China
  • Received:2015-04-30 Revised:2015-07-03 Published:2020-07-03

摘要: 大型场馆的人员疏散问题实际上是一个多目标的优化问题,要求达到疏散时间短、疏散路径长度小、拥挤度低等目标,而由于约束条件之间的冲突性,使多个目标同时达到最优是困难的。目前主要的求解方法是利用智能进化算法进行启发式搜索和解的偏序关系为特征的演化多目标优化算法求解。布谷鸟算法是在布谷鸟寻窝产卵的行为中发现了一种新的搜索算法,基本的布谷鸟算法的搜索活力不足、搜索偏慢。从改变布谷鸟算法的搜索多样性等方面着手提高布谷鸟算法在优化问题上的求解能力,将新算法用于人群疏散的多目标优化,取得了较好的效果

关键词: 疏散模型, 布谷鸟算法, 人群疏散, 多目标优化

Abstract: The crowd evacuation problem is a multi-objective optimization problem in large public places under the emergency, but because of the conflict between multiple objectives in multi-objective optimization problem, it is difficult to make the multiple targets achieve the optimal at the same time. The most popular solution is an evolution multi objective optimization algorithm for the characteristics of heuristic search of population and the partial order relation. Cuckoo search algorithm is a new search algorithm which was found in the behavior of cuckoo nest spawning lies, the basic cuckoo search algorithm is lack of vitality, and search is slow. From the change of cuckoo search algorithm search diversity to improve the ability to solve the cuckoo algorithm in optimization problems, a new algorithm was applied to multi-objective optimization of crowd evacuation, which has achieved good results.

Key words: evacuation model, cuckoo search algorithm, crowd evacuation, multi-objective optimization

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