基于改进多目标布谷鸟算法的水资源配置研究

为有效求解考虑水库调度的多目标水资源配置问题,充分实现有限水资源的科学利用,提出一种改进的多目标布谷鸟算法(IMOCS),与传统布谷鸟算法相比,IMOCS引入了混沌理论以保证初始种群的多样性,利用自适应发现概率和步长以平衡算法全局寻优和局部搜索,并采用3-点最短路径法作为外部档案集删除和保留机制,以保证非支配解的均匀性和多样性。将改进的算法用于"山西大水网"背景下的同朔供水区,结果合理有效,验证了模型的可行性,为该区域水资源配置提供了一定的依据。

Water Resources Allocation Based on Improved Multi-objective Cuckoo Search

In order to effectively solve the multi-objective water resources allocation problem,this paper considers reservoir operation and fully realizes the scientific utilization of limited water resources, an improved multi-objective cuckoo search(IMOCS) is proposed in this paper. Compared with traditional cuckoo search, IMOCS introduces chaos theory to ensure the diversity of initial population, and uses adaptive discovery probability and step size to balance the global optimization and local search of the algorithm. In order to ensure the uniformity and diversity of the non-dominated solutions, the 3-point shortest path method is used as the deletion and preservation mechanism of the external archive set. In this paper, the improved algorithm is applied to Tongshuo Water Supply Area under the background of Shanxi water networks. The results are reasonable and effective, which verifies the feasibility of the model and provides a basis for water resources allocation in this area.