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A dual-randomness bi-level interval multi-objective programming model for regional water resources management

机译:区域水资源管理的双随机性双级间隔多目标规划模型

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摘要

In this research, a dual-randomness bi-level interval multi-objective programming (DR-BIMP) model was developed for supporting water resources management among multiple water sectors under complexities and uncertainties. Techniques of bi-level multi-objective programming (BMOP), double-sided stochastic chance constrained programming (DSCCP), and interval parameter programming (IPP) were incorporated into an integrated modeling framework to achieve comprehensive consideration of the complexities and uncertainties of water resources management systems. The DR-BIMP model can not only effectively deal with the interactive effects between multiple decision-makers in complex water management systems through the bi-level hierarchical strategies, but also can characterize the multiple uncertainties information expressed as interval format and probability density functions. It could thus improve upon the existing bi-level multi-objective programming through addressing discrete interval parameters and dual-randomness problems in optimization processes simultaneously. Then, the developed model was applied to a real-world case to optimally allocate water resources among three different water sectors in five sub-regions in the Dongjiang River basin, south China. The results of the model include determining values, interval values, and stochastic distribution information, which can assist bi-level decision-makers to plan future resources effectively to some extent. After comparing the variations of results, it is found that an increasing probability level can lead to higher system benefits, which is increased from [20,786.00, 26,425.92] x 10(8) CNY to [22,290.84, 27,492.57] x 10(8) CNY, while the Gini value is reduced from [0.365, 0.446] to [0.345, 0.405]. A set of increased probability levels gives rise to the lower-level objectives. Furthermore, the advantages of the DR-BIMP model were highlighted by comparing with the other models originated from the developed model. The comparison results indicated that the DR-BIMP model was a valuable tool for generating a range of decision alternatives and thus assists the bi-level decision-makers to identify the desired water resources allocation schemes under multiple scenarios.
机译:在本研究中,开发了一种双随机性双级间隔多目标编程(DR-BIMP)模型,用于在复杂性和不确定性下支持多个水部门之间的水资源管理。双层多目标编程(BMOP),双面随机机会约束编程(DSCCP)和间隔参数编程(IPP)的技术被纳入了集成的建模框架,以实现对水资源复杂性和不确定性的全面考虑管理系统。 DR-BIMP模型不仅可以通过BI级层级策略有效地处理复杂水管理系统中的多个决策者之间的互动效果,而且还可以表征为间隔格式和概率密度函数表示的多个不确定性信息。因此,它可以通过在优化过程同时寻址离散间隔参数和双随机性问题来改善现有的双级多目标编程。然后,将开发的模型应用于真实世界的案例,以在东江流域的五个子地区最佳地分配水资源。该模型的结果包括确定值,间隔值和随机分布信息,可以帮助双级决策者在某种程度上有效地规划未来资源。在比较结果的变化之后,发现增加的概率水平可以导致更高的系统益处,从[20,786.00,26,425.92] x 10(8)CNY至[22,290.84,27,492.57] x 10(8)CNY,虽然基尼值从[0.365,0.446]到[0.345,0.405]减少。一组增加的概率水平导致较低级别的目标。此外,通过与源自开发模型的其他模型相比,突出了DR-BIMP模型的优点。比较结果表明,DR-BIMP模型是一种有价值的工具,用于产生一系列决策替代品,从而有助于双级决策者识别多种情况下所需的水资源分配方案。

著录项

  • 来源
    《Journal of Contaminant Hydrology 》 |2021年第8期| 103816.1-103816.14| 共14页
  • 作者单位

    Guangdong Univ Technol Inst Environm & Ecol Engn Guangdong Prov Key Lab Water Qual Improvement & E Waihuan West Rd 100 Guangzhou 510006 Peoples R China|Southern Marine Sci & Engn Guangdong Lab Guangzho Guangzhou 511458 Peoples R China;

    Guangdong Univ Technol Inst Environm & Ecol Engn Guangdong Prov Key Lab Water Qual Improvement & E Waihuan West Rd 100 Guangzhou 510006 Peoples R China|Southern Marine Sci & Engn Guangdong Lab Guangzho Guangzhou 511458 Peoples R China;

    Guangdong Univ Technol Inst Environm & Ecol Engn Guangdong Prov Key Lab Water Qual Improvement & E Waihuan West Rd 100 Guangzhou 510006 Peoples R China|Southern Marine Sci & Engn Guangdong Lab Guangzho Guangzhou 511458 Peoples R China;

    Guangdong Univ Technol Inst Environm & Ecol Engn Guangdong Prov Key Lab Water Qual Improvement & E Waihuan West Rd 100 Guangzhou 510006 Peoples R China|Southern Marine Sci & Engn Guangdong Lab Guangzho Guangzhou 511458 Peoples R China;

    Guangdong Univ Technol Inst Environm & Ecol Engn Guangdong Prov Key Lab Water Qual Improvement & E Waihuan West Rd 100 Guangzhou 510006 Peoples R China|Southern Marine Sci & Engn Guangdong Lab Guangzho Guangzhou 511458 Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Water resources management; Complexities and uncertainties; Bi-level multi-objective programming; Double-sided stochastic chance-constrained programming; Interval parameter programming;

    机译:水资源管理;复杂性和不确定因素;双级多目标规划;双面随机机会约束编程;间隔参数编程;

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