基于蚁群-粒子群混合算法的水资源优化配置研究

发布时间：2018-01-15 19:04

本文关键词：基于蚁群-粒子群混合算法的水资源优化配置研究　出处：《西北农林科技大学学报(自然科学版)》2015年01期 　论文类型：期刊论文

【摘要】：【目的】对区域水资源的合理优化配置进行研究,为区域经济的发展、水资源的合理开发利用和节水型社会的建立提供参考。【方法】建立以经济、社会、生态环境效益为目标函数,各目标加权和为最优解的水资源优化配置模型,采用蚁群-粒子群混合算法对模型进行求解,并对渭北工业区进行水资源优化配置的实例分析,通过原供水量与优化配置水量的比较验证所建立模型的合理性。【结果】经计算,75%保证率下渭北工业区水资源的配置结果为:2015年地表水、地下水、外调水、中水供水量分别为1 747.30,13 244.84,12 905.95和1 060.23万m3;2020年各水源供水量分别为2 019.19,12 214.42,23 530.42和1 798.60万m3;与原始供水量相比,2015年和2020年总供水量分别减少312.73和421.11万m3,表现在农业供水量减少,生活、工业、生态用水均达到供需平衡。【结论】基于蚁群-粒子群混合算法的水资源优化配置结果合理,可作为研究区水资源合理开发利用决策的参考;蚁群-粒子群混合算法收敛速度快,寻优性能优越,可用于水资源优化配置的分析。
[Abstract]:[Objective] to study the optimal allocation of regional water resources, for the development of regional economy, reasonable exploitation and utilization of water resources and water-saving society provides the reference for the establishment. [method] to establish economic, social, ecological and environmental benefit as the objective function, the target weight and optimal allocation of water resources is the optimal solution of the model, the ant colony particle swarm algorithm to solve the model, and the Weibei industrial zone for example analysis of the optimal allocation of water resources, by comparing the original verification water supply and optimal allocation of water to the rationality of the model. [result] after calculation, 75% guarantee rates in Weibei industrial zone of water resources allocation results 2015: surface water, groundwater, water transfer, water supply was 1 747.30,13 905.95 244.84,12 and 10 million 602 thousand and 300 m3; the water supply in 2020 is 2 019.19,12 214.42,23 530.42 and 1798.6 respectively. 0 000 m3; compared with the original water supply, the total water supply in 2015 and 2020 respectively by 312.73 and 4 million 211 thousand and 100 m3, in the agricultural water supply to reduce the amount of life, industry, ecological water reached the balance of supply and demand. [Conclusion] Based on ant colony particle swarm algorithm for the optimal allocation of water resources is reasonable, can be used as water resources research in the rational development and utilization of reference for decision making; ant colony particle swarm optimization algorithm has a fast convergence speed, superior performance, can be used for the analysis of optimal allocation of water resources.

【作者单位】：西安理工大学水利水电学院;
【基金】：国家自然科学基金项目(51079120,51209170) 陕西省教育厅2010年省级重点实验室项目(2010JS077)
【分类号】：TV213.4
【正文快照】： 随着人口的增长及社会经济的发展,区域需水量不断增加,水资源供需矛盾日益突出,水资源短缺已由区域性问题逐步恶化成为全球性问题[1],水将成为21世纪可持续发展的严重制约因素。因此,水资源已不仅仅是人类生存的基础性资源,也是人类生存的战略性资源。为了缓解水资源缺乏给人

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