摘要
针对传统布谷鸟(CS)算法在求解配送中心选址问题时易陷入局部搜索不充分、搜索精度低、收敛性差的缺陷,提出一种改进的布谷鸟(HICS)算法。通过对步长及发现概率的改进,不仅可以避免陷入局部最优、收敛性差的缺陷,而且可以兼顾算法的整体寻优和局部搜索能力;同时利用Halton序列产生随机数,可以增加种群的多样性,进一步提高算法的搜索精度。在此基础上,以A省电力公司物资配送中心选址为例进行仿真实验,结果表明,改进的布谷鸟算法在求解电力物资配送中心选址问题上要优于布谷鸟算法以及其他智群算法,这对电力物资配送中心选址决策具有重要指导意义。
When solving the logistics distribution center location problem, traditional algorithms always fall into inadequate local search and low search accuracy and poor convergence performance. In view of this situation, this study presented an improved cuckoo search（HICS） algorithm. Firstly, the step-size factor and the discovery probability were improved to balance the local optimization and global optimization. On this basis, a random number is selected based on the Halton series. A case study using the improved cuckoo algorithm based on Halton series showed that the improved cuckoo algorithm converges faster and has better results than the traditional one. The improved cuckoo algorithm based on Halton series is much better, which is of great significance for the construction of material distribution centers of electric power enterprises.
作者
王喜平
郄少媛
赵齐
WANG Xiping;QIE Shaoyuan;ZHAO Qi(School of Economy and Management,North China Electric Power University,Baoding 071003,China;Technical Application Research Center China Post Research Institute,Beijing 100096,China)
出处
《电力科学与工程》
2018年第10期1-7,共7页
Electric Power Science and Engineering
关键词
布谷鸟算法
物资配送中心
选址
电力公司
Cuckoo algorithm
material distribution center
location
electric power enterprise
