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Alternative Approaches for Solving the Sensor Placement Prob- lem in Large Networks

机译:解决大型网络中传感器放置问题的替代方法

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Positioning sensors in a water supply network is a NP-hard task. We propose three algorithms - one based on integer linear programming (ILP) and the other two based on the Greedy paradigm. We apply these algorithms to real case networks and compare the results of these algorithms with the results of an algorithm based on NSGA II, a genetic algorithm. We come to the conclusion that our algorithms outperform NSGA II in every single case. The algorithm based on linear integer programming may be applied as a competitor to the algorithm implemented in TEVA -SPOT (Berry, 2009), while the first Greedy algorithm may replace the ILP algorithm in large networks due to its faster running time. The second Greedy algorithm approaches the question on finding those nodes which are the most sensitive to variations in pressure and are thereby ideal places to monitor the hydraulic state of a water distribution network.
机译:在供水网络中定位传感器是一项艰巨的任务。我们提出了三种算法-一种基于整数线性规划(ILP),另一种基于Greedy范式。我们将这些算法应用于实际案例网络,并将这些算法的结果与基于遗传算法NSGA II的算法的结果进行比较。我们得出的结论是,在每种情况下,我们的算法均优于NSGA II。基于线性整数规划的算法可以作为TEVA-SPOT中实现的算法的竞争者(Berry,2009),而第一个Greedy算法由于运行时间较快而可以代替大型网络中的ILP算法。第二种贪婪算法解决了以下问题:找到对压力变化最敏感的那些节点,从而成为监视供水网络水力状态的理想场所。

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