The present study suggests an integrated approach for determining the optimal release policy for the Mula reservoir situated at the Godavari basin, India. The proposed integrated algorithm named DP-PSO is a hybridization of Dynamic Programming (DP) and Particle Swarm Optimization (PSO). The reservoir operation problem is demonstrated in the form of a nonlinear optimization model subject to various constraints. Two case studies are considered. In the first case the efficiency of the proposed algorithm is tested on a small data set of 1 year and in the second case, data set taken is for 10 years. The results obtained are compared in terms of objective function value as well CPU time for performance evaluation of the integrated methods.

中文翻译：

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水库调度动态规划集成粒子群优化算法

本研究提出了一种综合方法，用于确定位于印度戈达瓦里盆地的穆拉水库的最佳释放策略。提出的称为DP-PSO的集成算法是动态规划（DP）和粒子群优化（PSO）的混合。储层运行问题以受各种约束的非线性优化模型的形式证明。考虑了两个案例研究。在第一种情况下，在1年的小数据集上测试了所提出算法的效率，在第二种情况下，所使用的数据集是10年。将获得的结果在目标函数值以及CPU时间方面进行比较，以评估集成方法的性能。