A multiobjective optimization(MOP)control method for integrated urban drainage systems(UDSs)was proposed to mitigate the impact of overflow pollution on ecosystems.Existing research often targets single rainfall event...A multiobjective optimization(MOP)control method for integrated urban drainage systems(UDSs)was proposed to mitigate the impact of overflow pollution on ecosystems.Existing research often targets single rainfall events,individual objectives,or isolated facilities,lacking a comprehensive,long-term strategy.To address this,the proposed method incorporates long-term rainfall data to optimize performance across key system components in the UDSs,including drainage pipelines,pumping stations,detention pipelines,intelligent diversion wells(IDWs)and sewage treatment plants(STPs).This MOP approach dynamically coordinates infrastructure to reduce combined sewer overflows(CSOs)and pollutant loads while balancing operational costs and facility performance.Applied to a case study of Yuhang District,Hangzhou,China under a six-month rainfall sequence,the method achieved average CSOs reduction rates of 47.87%under moderate rain and 33.60%under heavy rain,with corresponding pollutant discharge reductions of 77.55%and 71.37%.The optimization also improved pumping stations efficiency,reducing operating hours by 13.76%.Key IDWs influencing system performance were recognized,with IDWs 9,10,and 14 being the most critical.These results indicate that this approach can significantly improve the long-term hydraulic and environmental performance of UDSs,offering theoretical insights and practical guidance for sustainable urban water management.展开更多
In this paper we study the problem of locating multiple facilities in convex sets with fuzzy parameters. This problem asks to find the location of new facilities in the given convex sets such that the sum of weighted ...In this paper we study the problem of locating multiple facilities in convex sets with fuzzy parameters. This problem asks to find the location of new facilities in the given convex sets such that the sum of weighted distances between new facilities and existing facilities is minimized. We present a linear programming model for this problem with block norms, then we use it for problems with fuzzy data. We also do this for rectilinear and infinity norms as special cases of block norms.展开更多
基金supported by the Major Project of National Natural Science Foundation of China(No.52091544).
文摘A multiobjective optimization(MOP)control method for integrated urban drainage systems(UDSs)was proposed to mitigate the impact of overflow pollution on ecosystems.Existing research often targets single rainfall events,individual objectives,or isolated facilities,lacking a comprehensive,long-term strategy.To address this,the proposed method incorporates long-term rainfall data to optimize performance across key system components in the UDSs,including drainage pipelines,pumping stations,detention pipelines,intelligent diversion wells(IDWs)and sewage treatment plants(STPs).This MOP approach dynamically coordinates infrastructure to reduce combined sewer overflows(CSOs)and pollutant loads while balancing operational costs and facility performance.Applied to a case study of Yuhang District,Hangzhou,China under a six-month rainfall sequence,the method achieved average CSOs reduction rates of 47.87%under moderate rain and 33.60%under heavy rain,with corresponding pollutant discharge reductions of 77.55%and 71.37%.The optimization also improved pumping stations efficiency,reducing operating hours by 13.76%.Key IDWs influencing system performance were recognized,with IDWs 9,10,and 14 being the most critical.These results indicate that this approach can significantly improve the long-term hydraulic and environmental performance of UDSs,offering theoretical insights and practical guidance for sustainable urban water management.
文摘In this paper we study the problem of locating multiple facilities in convex sets with fuzzy parameters. This problem asks to find the location of new facilities in the given convex sets such that the sum of weighted distances between new facilities and existing facilities is minimized. We present a linear programming model for this problem with block norms, then we use it for problems with fuzzy data. We also do this for rectilinear and infinity norms as special cases of block norms.
