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PADDS Algorithm Assessment for Biobjective Water Distribution System Benchmark Design Problems

机译:双目标给水系统基准设计问题的PADDS算法评估

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Two implementations of the Pareto archived dynamically dimensioned search (PADDS) algorithm using different selection metrics are applied to 12 water distribution network (WDN) design benchmark problems from the literature. Convex hull contribution (CHC) and hypervolume contribution (HVC) are used as selection metrics for PADDS making this study the first to assess their relative performance on WDN design problems. Past research applied five state-of-the-art multiobjective evolutionary algorithms (MOEAs) to these 12 benchmark problems to generate the best-known Pareto fronts (PFs). The PADDS-CHC and PADDS-HVC both find all solutions on the known true PFs of the first three problems. Together, both PADDS results augment the previously best-known PFs in the nine other benchmark problems with new PF solutions, some of which dominate previous best-known PF solutions, to define updated best-known PFs. Comparative results against five state-of-the-art MOEAs show PADDS derived best-known PFs are equal or better than all other algorithms in 11 of 12 WDN design problems. A comprehensive comparison between PADDS-CHC and PADDS-HVC performance on the largely convex benchmark problem Pareto fronts reveals the different responses of PADDS algorithm to increment of computational budget. An innovative measure called effective archive size (EAS) is introduced to quantify the portion of PADDS archived solutions that play the dominant role in directing PADDS toward the final PF. Tracking the EAS value throughout the search revealed that compared with PADDS-HVC, the EAS of PADDS-CHC is typically close to an order of magnitude smaller. In fact, the PADDS-CHC algorithm generates candidate solutions from a surprisingly small effective archive size that ranges from only 16 to 73 solutions across the 12 benchmark WDN problems while being only 24 for the largest problem. (C) 2017 American Society of Civil Engineers.
机译:使用不同的选择度量标准的帕累托档案动态尺寸搜索(PADDS)算法的两种实现方式被应用于文献中的12个水分配网络(WDN)设计基准问题。凸包贡献(CHC)和超体积贡献(HVC)用作PADDS的选择指标,使本研究首次评估了它们在WDN设计问题上的相对性能。过去的研究对这12个基准问题应用了五种最新的多目标进化算法(MOEA),以产生最著名的帕累托前沿(PF)。 PADDS-CHC和PADDS-HVC都可以找到前三个问题的已知真实PF的所有解决方案。两种PADDS结果一起,通过新的PF解决方案扩展了其他九个基准问题中的先前最知名的PF,其中一些控制了先前最知名的PF解决方案,以定义更新的最知名PF。与五个最新MOEA的比较结果表明,在12个WDN设计问题中的11个中,PADDS派生的最知名PF等于或优于所有其他算法。通过对PADDS-CHC和PADDS-HVC性能在很大程度上凸的基准问题Pareto前沿进行的全面比较,揭示了PADDS算法对计算预算增加的不同响应。引入了一种称为有效档案大小(EAS)的创新措施,以量化PADDS档案解决方案中在将PADDS引向最终PF方面起主导作用的部分。在整个搜索过程中跟踪EAS值表明,与PADDS-HVC相比,PADDS-CHC的EAS通常接近小一个数量级。实际上,PADDS-CHC算法从令人惊讶的小有效存档大小生成候选解决方案,该解决方案在12个基准WDN问题中仅从16到73个解决方案,而对于最大问题只有24个。 (C)2017年美国土木工程师学会。

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