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Non-Dominated Sorting Harmony Search Differential Evolution (NS-HS-DE): A Hybrid Algorithm for Multi-Objective Design of Water Distribution Networks

机译:非支配排序和谐搜索差分进化(NS-HS-DE):配水管网多目标设计的混合算法

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摘要

We developed a hybrid algorithm for multi-objective design of water distribution networks (WDNs) in the present study. The proposed algorithm combines the global search schemes of differential evolution (DE) with the local search capabilities of harmony search (HS) to enhance the search proficiency of evolutionary algorithms. This method was compared with other multi-objective evolutionary algorithms (MOEAs) including NSGA2, SPEA2, MOEA/D and extended versions of DE and HS combined with non-dominance criteria using several metrics. We tested the compared algorithms on four benchmark WDN design problems with two objective functions, (i) the minimization of cost and (ii) the maximization of resiliency as reliability measure. The results showed that the proposed hybrid method provided better optimal solutions and outperformed the other algorithms. It also exhibited significant improvement over previous MOEAs. The hybrid algorithm generated new optimal solutions for a case study that dominated the best-known Pareto-optimal solutions in the literature
机译:在本研究中,我们开发了一种用于水分配网络(WDN)多目标设计的混合算法。所提出的算法结合了差分进化(DE)的全局搜索方案与和声搜索(HS)的局部搜索能力,以提高进化算法的搜索能力。将该方法与其他多目标进化算法(MOEA)进行了比较,包括NSGA2,SPEA2,MOEA / D以及DE和HS的扩展版本以及使用几种度量的非主导标准。我们在具有两个目标函数的四个基准WDN设计问题上测试了比较的算法:(i)最小化成本和(ii)最大化弹性作为可靠性度量。结果表明,所提出的混合方法提供了更好的最优解,并且优于其他算法。与以前的MOEA相比,它也显示出显着的改进。混合算法为案例研究生成了新的最优解,该案例主导了文献中最著名的帕累托最优解

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