A Hybrid Water Distribution Networks Design Optimization Method Based on a Search Space Reduction Approach and a Genetic Algorithm
A Hybrid Water Distribution Networks Design Optimization Method Based on a Search Space Reduction Approach and a Genetic Algorithm
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基于搜索空间缩减法和遗传算法的混合配水管网设计优化方法
DOI：
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发表时间：
2017
期刊：
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通讯作者：
R. López
中科院分区：
文献类型：
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作者：
J. Reca;J. Martínez;R. López
这项工作提出了一种新的方法，以提高效率的数学方法应用于供水系统的优化设计。该方法是基于减少搜索空间的限制，可以用于每个网络管道的直径。为了缩小搜索空间，分析了两种相反的极端流量分布情况，然后对管流施加速度限制。第一种情况在网络中产生最均匀的流量分布。相反的情况由具有最大流量累积的网络表示。这两个极端流量分布计算通过解决二次规划问题，这是一个非常强大和有效的程序。这种方法已被耦合到遗传算法（GA）。GA具有整数编码方案和取决于速度限制内包括的直径的数量的可变数量的等位基因。该方法已被应用到几个基准网络和它的性能进行了比较，一个经典的GA制定一个非有界的搜索空间。它大大减少了搜索空间，并提供了一个更快，更准确的收敛比GA配方。这种方法也可以耦合到其他元分析。
This work presents a new approach to increase the efficiency of the heuristics methods applied to the optimal design of water distribution systems. The approach is based on reducing the search space by bounding the diameters that can be used for every network pipe. To reduce the search space, two opposite extreme flow distribution scenarios are analyzed and velocity restrictions to the pipe flow are then applied. The first scenario produces the most uniform flow distribution in the network. The opposite scenario is represented by the network with the maximum flow accumulation. Both extreme flow distributions are calculated by solving a quadratic programming problem, which is a very robust and efficient procedure. This approach has been coupled to a Genetic Algorithm (GA). The GA has an integer coding scheme and variable number of alleles depending on the number of diameters comprised within the velocity restrictions. The methodology has been applied to several benchmark networks and its performance has been compared to a classic GA formulation with a non-bounded search space. It considerably reduced the search space and provided a much faster and more accurate convergence than the GA formulation. This approach can also be coupled to other metaheuristics.