摘要
针对城市供水管网压力监测点的优化布置问题,以监测范围最大化为目标,结合节点间的水压相关性和水压敏感度构建监测点优化布置模型,将实际问题转化为一个单目标组合优化问题。以东南沿海某城镇供水主干管网为例,利用2种群体智能优化算法——蝙蝠算法(BA)和粒子群算法(PSO)对模型进行求解。将两种算法的运行结果进行了多方面对比,发现BA因其全局寻优能力强,计算代时较短,在监测点优化布置问题中展现了更为出色的搜索精度和效率。
Aiming at the optimal arrangement of pressure monitoring points in urban water supply network,the optimal arrangement model of pressure monitoring points was established by taking the maximization of monitoring range as the target and combining water pressure correlation and water pressure sensitivity between nodes,and the practical problem was transformed into a single-objective combinatorial optimization problem.Two swarm intelligence optimization algorithms—bat algorithm and particle swarm algorithm were applied in a water supply network of a town in southeastern coast to solve the model.The operational results of the two algorithms were compared in many aspects.Bat algorithm,which had strong global search ability and short computation time,had shown excellent search accuracy and efficiency in the optimal location of monitoring points.
作者
岳宏宇
吕谋
李红卫
刘志壮
种宇飞
YUE Hong-yu;Lü Mou;LI Hong-wei;LIU Zhi-zhuang;CHONG Yu-fei(School of Environmental and Municipal Engineering,Qingdao University of Technology,Qingdao 266033,China)
出处
《中国给水排水》
CAS
CSCD
北大核心
2020年第21期66-70,共5页
China Water & Wastewater
基金
国家自然科学基金资助项目(51778307)
山东省重点研发计划项目(GG201809260435)。
关键词
供水管网
压力监测点
群体智能优化算法
组合优化
water supply network
pressure monitoring point
swarm intelligence optimization algorithm
combined optimization
