摘要
针对当前算法求解物流配送中心选址问题时,普遍存在求解精度不高、速度较慢和规模较小等缺点,提出一种改进花朵授粉算法的智能求解方法。首先根据物流配送中心模型的特点将花朵授粉算法进行离散化,设计整数编码,再结合遗传算子的选择、交叉和逆转操作进行局部搜索。将花朵授粉算法的全局搜索与遗传算子的局部搜索融合,通过4个不同规模的仿真实验表明所提出的算法在求解精度、速度和规模上较其他算法具有优势,而且规模越大,改进算法的效果越明显,对中等规模的物流选址问题提供了一种较好的寻址方案。
Aiming to current algorithms for choosing logistics distribution center location,there are many shortcomings such as low accuracy,slow speed and small scale in solving problems.A modified flower pollination algorithm was presented for solving the problem of logistics distribution center location.According to the characteristic of logistics distribution center location model,the flower pollination algorithm was discretized,and the integer coding was designed to search locally,combining the selection,crossing and reverse of genetic operators.Integrating the global search of flower pollination algorithms with the local search of genetic operators,the simulation experiments of four different scales were carried out.It indictes that the proposed algorithm has advantages in solving accuracy,speed and scale,especially for the problem of large-scale structures,and the superiority of improved method was much more obvious.It provids a better scheme for choosing the logistics distribution center location of medium-scale.
作者
刘敏
Liu Min(College of Information Engineering, Guangxi University of Foreign Languages, Nanning 530222, Guangxi, China)
出处
《计算机应用与软件》
北大核心
2019年第6期277-281,316,共6页
Computer Applications and Software
基金
广西哲学社会科学规划课题(17FTY010)
关键词
物流配送中心选址
花朵授粉算法
遗传算子
Logistics distribution center location choice
Flower pollination algorithm
Genetic operators