| 基于混合微粒群优化算法的配送中心选址问题求解 |
| |
| 引用本文： | 李军军,王锡淮,黄有方,肖健梅.基于混合微粒群优化算法的配送中心选址问题求解[J].物流科技,2006,29(8):26-30. |
| |
| 作者姓名： | 李军军 王锡淮 黄有方 肖健梅 |
| |
| 作者单位： | 上海海事大学,上海,200135 |
| |
| 基金项目： | 上海市教委资助项目;上海市重点学科建设项目 |
| |
| 摘 要： | 将微粒群优化算法和模拟退火算法结合．针对配送中心选址问题．构造了微粒表达方法。提出了此问题的一种混合微粒群优化算法。通过整数规范化。微粒群能在整数空间内对问题进行优化求解。该算法能克服基本微粒群优化算法精度较低，易发散的缺点，有较高的搜索效率。经过实验仿真，与基本微粒群优化算法、遗传算法进行比较．证明了该算法的有效性。
|
| 关 键 词： | 配送中心选址 微粒群优化算法 模拟退火 整数规范化 |
| 文章编号： | 1002-3100（2006）08-0026-05 |
| 收稿时间： | 2006-03-08 |
| 修稿时间： | 2006年3月8日 |
Solving Location Problem of Distribution Centre Based on Hybrid Particle Swarm Optimization Algorithm |
| |
| I Jun-jun,WANG Xi-huai,HUANG You-fang,XIAO Jian-mei.Solving Location Problem of Distribution Centre Based on Hybrid Particle Swarm Optimization Algorithm[J].Logistics Management,2006,29(8):26-30. |
| |
| Authors: | I Jun-jun WANG Xi-huai HUANG You-fang XIAO Jian-mei |
| |
| Institution: | Shanghai Maritime University, Shanghai 200135, China |
| |
| Abstract: | A kind of coding is constructed for location problem of distribution center and then a hybrid particle swarm optimization algorithm is proposed.This algorithm integrates the particle swarm optimization with the simulated annealing algorithm.The particle swarm evolves in the integer space after being integer standardized. This algorithm can solve the problem of low precision and divergence of basic particle swarm optimization algorithm, so it has higher efficiency of search. It is compared with basic particle swarm optimization algorithm and genetic algorithm. Results prove that this algorithm is effective. |
| |
| Keywords: | location of distribution centre particle swarm optimization algorithm simulated annealing integer standardization |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
