摘要
通过分析水库防洪优化调度模型以及逐步优化算法(POA)在运算中常收敛于局部最优的缺陷,提出了一种基于水量平衡的改进算法,避免总决策序列在复杂的约束条件下被分隔成若干不相互作用的子序列,使得算法更具跳跃性,不易陷入局部最优。实例分析表明:在水库防洪优化调度中,改进后的算法基本上能够解决传统POA过于依赖初始解的问题,提高了全局搜索能力,并且加快了收敛速度,具有良好的实用价值和借鉴意义。
A flood control optimization model and progressive optimization algorithm( POA) 's defects that is easy to converge to local optimum during operations had been introduced briefly.This paper proposed an improved algorithm based on water balance,avoiding decision sequences separated into several non interacting subsequences under complex constraints. The algorithm itself had stronger bound and it was hard to trap in the local optimal value.The case study results demonstrate that comparing with traditional POA,improved algorithm can basically solve the problem that POA is strongly dependent on initial sequences. Furthermore,improved algorithm can also enhance the global search ability and convergence speed,which verified the algorithm's well practical value and reference.
引文
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