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.
翻译:重水分配网设计(WDND)优化问题在于确定水网的管道直径,以便满足水力限制并尽量减少总成本。传统上,这种设计决定是根据专家经验作出的。但是,当网络规模扩大时,大拇指规则将很少导致接近最佳的决定。在过去三十年中,已经开发了大量技术来解决最佳设计水分配网的问题。在本文中,我们处理NP-硬水分配网设计(WDND)优化问题,在出现不同需求模式的多期间环境中解决。我们提议一种新的模拟迭代本地搜索计量经济学,进一步探讨问题的结构,以获得高质量的解决方案。计算实验表明,我们的方法非常具有竞争力,因为它能够改进对大多数试验的状态的计量经济学。此外,它与低成本解决方案相交汇得更快,并显示出更强大的表现,因为它与最已知的解决方案的偏差较小。