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Intelligent Systems in Optimizing Reservoir Operation Policy: A Review

机译：智能系统优化水库调度策略研究进展

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The paper presents a survey of several optimization techniques, mainly artificial intelligences (AIs) which have been applied to the reservoir operation modelling whether its single or multi-reservoir system. The reservoir system modeling is essential for any nations and the optimal use of it is always asked. The main objective of this review article is to discuss the potentiality of the evolutionary algorithms (EAs) and the ability to integrate with other techniques which can provide the best results. Also the formulation of these types of application has described on the ground of a well known benchmark problem regarding this field. The traditional algorithms got some drawbacks. The study provides a complete understanding to the EA users about next generation optimal search procedure and help to overcome the drawbacks. Though the background of application number of swarm intelligences is less comparatively than the genetic algorithm (GA), it provides a great scope for the researcher for further development. Also comparative results with other popular methods (such as, linear programming, stochastic dynamic programming) are discussed on the basis of past research results. Conclusions and suggestive remarks are made for the help of researchers and the reservoir decision makers as well.
机译：本文介绍了几种优化技术的概况，主要是人工智能（AI），这些技术已应用于单层或多层储层系统的油藏运行模型。水库系统建模对于任何国家都是必不可少的，并且始终要求对其进行最佳使用。本文的主要目的是讨论进化算法（EA）的潜力以及与其他能够提供最佳结果的技术集成的能力。同样，基于与该领域有关的众所周知的基准问题描述了这些类型的应用的配方。传统算法存在一些弊端。该研究为EA用户提供了有关下一代最佳搜索程序的完整理解，并有助于克服这些缺点。尽管群体智能的应用背景与遗传算法（GA）相比相对较少，但为研究人员的进一步发展提供了广阔的空间。在过去的研究成果的基础上，还讨论了与其他流行方法（例如线性规划，随机动态规划）的比较结果。结论和暗示性的评论对研究人员和储层决策者也有帮助。

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