基于改进模拟的迭代局部搜索元启发式重力给水管网优化设计
An enhanced simulation-based iterated local search metaheuristic for gravity fed water distribution network design optimization
摘要：
重力给水管网优化设计问题是指在满足水力约束条件的前提下，以总投资最小为目标，确定管网的管径。传统上，这种设计决策是根据专家经验做出的。然而，当网络规模扩大时，经验法则很少会导致接近最优的决策。在过去的三十年里，已经开发了大量的技术来解决优化设计配水网络的问题。在本文中，我们解决了NP-硬配水网络设计（WDND）优化问题，在多个周期设置时变需求模式发生。我们提出了一个新的基于模拟的迭代局部搜索元启发式算法，进一步探讨了问题的结构，试图获得高质量的解决方案。计算实验表明，我们的方法是非常有竞争力的，因为它是能够提高超过一个国家的最先进的元启发式的大多数执行的测试。此外，它收敛到低成本的解决方案更快，并表现出更强大的性能，因为它获得了最佳已知的解决方案的偏差较小。
英文摘要：
The gravity fed water distribution network design (WDND) optimization problem consists in determining the pipe diameters of a water network such that hydraulic constraints are satisfied and the total cost is minimized. Traditionally, such design decisions are made on the basis of expert experience. When networks increase in size, however, rules of thumb will rarely lead to near optimal decisions. Over the past thirty years, a large number of techniques have been developed to tackle the problem of optimally designing a water distribution network. In this paper, we tackle the NP-hard water distribution network design (WDND) optimization problem in a multi-period setting where time varying demand patterns occur. We propose a new simulation-based iterated local search metaheuristic which further explores the structure of the problem in an attempt to obtain high quality solutions. Computational experiments show that our approach is very competitive as it is able to improve over a state-of-the-art metaheuristic for most of the performed tests. Furthermore, it converges much faster to low cost solutions and demonstrates a more robust performance in that it obtains smaller deviations from the best known solutions.
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