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Optimal operation of cascade reservoirs based on generalized ant colony optimization method

机译:基于广义蚁群优化方法的级联储层最佳运行

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An optimization algorithm is proposed by means of integrating the generalized ant colony optimization (GACO) with progressive optimal algorithm (POA), and is applied to the optimal operation of cascade reservoirs. This integrated algorithm possesses large scale search capability of generalized ant colony algorithm and better local search capability of progressive optimal algorithm at the same time. Therefore, under the condition of ensuring global convergence, high quality optimization solution can be searched quickly by the proposed algorithm. In order to increase the rapidity of convergence, initial ant colony is generated stochastically in an automatic way constrained by water mass balance equation. And a penalty function is utilized to handle the boundary conditions and other non-equality constraints. A case study is given to show the effectivity and practicability of the algorithm.
机译:通过将广义蚁群优化(GACO)与逐行最优算法(POA)集成,并应用于级联储层的最佳操作来提出优化算法。这种集成算法具有广义蚁群算法的大规模搜索能力,同时具有逐行最佳算法的更好的局部搜索能力。因此,在确保全局收敛的条件下,可以通过所提出的算法快速地搜索高质量优化解决方案。为了提高收敛的速度,以由水质量平衡方程的自动化方式随机生成初始蚁群。惩罚功能用于处理边界条件和其他非平等约束。给出了案例研究表明算法的有效性和实用性。

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