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State of the Art Review of Ant Colony Optimization Applications in Water Resource Management

机译:蚁群优化技术在水资源管理中的应用研究进展

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Among the emerged metaheuristic optimization techniques, ant colony optimization (ACO) has received considerable attentions in water resources and environmental planning and management during last decade. Different versions of ACO have proved to be flexible and powerful in solving number of spatially and temporally complex water resources problems in discrete and continuous domains with single and/or multiple objectives. Reviewing large number of peer reviewed journal papers and few valuable conference papers, we intend to touch the characteristics of ant algorithms and critically review their state-of- the-art applications in water resources and environmental management problems, both in discrete and continuous domains. The paper seeks to promote Opportunities, advantages and disadvantages of the algorithm as applied to different areas of water resources problems both in research and practice. It also intends to identify and present the major and seminal contributions of ant algorithms and their findings in organized areas of reservoir operation and surface water management, water distribution systems, urban drainage and sewer systems, groundwater managements, environmental and watershed management. Current trends and challenges in ACO algorithms are discussed and called for increased attempts to carry out convergence analysis as an active area of interest.
机译:在新兴的元启发式优化技术中,过去十年来,蚁群优化(ACO)在水资源和环境规划与管理方面受到了广泛关注。事实证明,不同版本的ACO在解决具有单个和/或多个目标的离散和连续域中的大量时空复杂的水资源问题方面具有灵活性和强大性。回顾大量同行评审的期刊论文和有价值的会议论文,我们打算探讨蚂蚁算法的特征,并严格审查其在离散和连续领域在水资源和环境管理问题中的最新应用。本文力图推广该算法在研究和实践中应用于水资源问题不同领域的机会,利弊。它还打算确定并介绍蚂蚁算法的主要和开创性贡献及其在水库运营和地表水管理,水分配系统,城市排水和下水道系统,地下水管理,环境和流域管理等有组织领域中的发现。讨论了ACO算法的当前趋势和挑战,并呼吁进行更多的尝试来进行收敛性分析,并将其作为一个活跃的领域。

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