Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (15): 237-240.DOI: 10.3778/j.issn.1002-8331.2009.15.069

• 工程与应用 • Previous Articles     Next Articles

Research on drain layout optimization using probability learning evolutionary algorithm

WAN Shan-shan,HAO Ying   

  1. School of Electricity and Information Engineering,Beijing Institute of Civil Architecture and Structure,Beijing 100044,China
  • Received:2008-04-01 Revised:2008-07-03 Online:2009-05-21 Published:2009-05-21
  • Contact: WAN Shan-shan

PBIL进化算法求解排污口布局优化问题的研究

万珊珊,郝 莹   

  1. 北京建筑工程学院 电气与信息工程学院,北京 100044
  • 通讯作者: 万珊珊

Abstract: The layout of drain plays an important role to the protection of water ecosystem and urban environment.In this paper the method of Population Based Incremental Learning algorithm(PBIL) is discussed to solve the optimization of drain layout.The main factors such as regional containing sewage capacity,sewage disposal capacity quantity limit of drains within specific area are considered as constraint conditions.Penalty function method is put forward to model the problem and object function is to guarantee economy benefit.The algorithm is applied to the drain layout engineering and the drain layout obtained though PBIL algorithm excels traditional method and it can protect the urban environment more efficiently and ensure the healthy development of water ecosystem more successfully.

Key words: Population Based Incremental Learning algorithm(PBIL), drain layout, optimization, development

摘要: 排污口的布局对水生态系统的良性发展和城市环境美化起着至关重要的作用。利用基于概率分析策略的PBIL算法,综合考虑影响排污口布局的区域地理条件、水环境容量、水域纳污能力、水生态资源等约束条件,并利用层次分析法确定影响因子的权重值。利用罚函数法构造了排污口优化设置问题的模型,设计了整数编码方式,并应用于工程实例。结果表明了该算法能较为准确合理地求解此类问题,为经济的可持续发展提供了较好的技术支持。

关键词: PBIL算法, 排污, 优化设置, 可持续发展