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Optimization of Water Resources Utilization by PSO-GA

机译:利用PSO-GA优化水资源利用

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摘要

The objective of this paper is to present an optimal model to address the water resources utilization of the Tao River basin in China. The Tao River water diversion project has been proposed to alleviate the problem of water shortages in Gansu Province in China. A multi reservoir system is under consideration with multiple objectives including water diversion, ecological water demand, irrigation, hydropower generation, industrial requirements, and domestic uses in the Tao River basin. A multi-objective model for the minimization of water shortages and the maximization of hydro-power production is proposed to manage the utilization of Tao River water resources. An adjustable PSO-GA (particle swarm optimization - genetic algorithm) hybrid algorithm is proposed that combines the strengths of PSO and GA to balance natural selection and good knowledge sharing to enable a robust and efficient search of the solution space. Two driving parameters are used in the adjustable hybrid model to optimize the performance of the PSO-GA hybrid algorithm by assigning a preference to either PSO or GA. The results show that the proposed hybrid algorithm can simultaneously obtain a promising solution and speed up the convergence.
机译:本文的目的是提出一种解决中国model河流域水资源利用的最优模型。提出了Tao河调水工程,以缓解中国甘肃省的水资源短缺问题。正在考虑建立一个具有多个目标的多水库系统,包括引水,生态需水,灌溉,水力发电,工业需求以及the河流域的生活用水。为了管理Tao河水资源的利用,提出了一个多目标的水短缺最小化和水力发电最大化模型。提出了一种可调整的PSO-GA(粒子群优化-遗传算法)混合算法,该算法结合了PSO和GA的优势来平衡自然选择和良好的知识共享,从而能够对解决方案空间进行鲁棒而有效的搜索。通过将优先级分配给PSO或GA,可调整混合模型中使用了两个驱动参数来优化PSO-GA混合算法的性能。结果表明,提出的混合算法可以同时获得有希望的解决方案并加快收敛速度​​。

著录项

  • 来源
    《Water Resources Management》 |2013年第10期|3525-3540|共16页
  • 作者单位

    Institute of Water Resources and Hydroelectric Power, Xi'an University of Technology, Xi'an, Shaanxi, China;

    Institute of Water Resources and Hydroelectric Power, Xi'an University of Technology, Xi'an, Shaanxi, China;

    Institute of Water Resources and Hydroelectric Power, Xi'an University of Technology, Xi'an, Shaanxi, China;

    Institute of Water Resources and Hydroelectric Power, Xi'an University of Technology, Xi'an, Shaanxi, China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Multi-objective optimization model; Water resources; Reservoir operation; PSO-GA;

    机译:多目标优化模型;水资源;水库作业;遗传算法;

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