[1]黄丹华,王肃.基于混合粒子群算法的货位优化分配问题[J].应用科技,2013,40(04):9-13.[doi:10.3969/j.issn.1009-671X.2012.201306013]
 HUANG Danhua,WANG Su.A hybrid particle swarm optimization algorithm for storage allocation optimization problem[J].Applied science and technology,2013,40(04):9-13.[doi:10.3969/j.issn.1009-671X.2012.201306013]
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基于混合粒子群算法的货位优化分配问题(/HTML)
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《应用科技》[ISSN:1009-671X/CN:23-1191/U]

卷:
第40卷
期数:
2013年04期
页码:
9-13
栏目:
自动化技术
出版日期:
2013-10-05

文章信息/Info

Title:
A hybrid particle swarm optimization algorithm for storage allocation optimization problem
文章编号:
1009- 671X(2013)04- 0009- 05
作者:
黄丹华1王肃2
1.华东政法大学 图书馆,上海 200042; 2.华东师范大学 计算中心,上海 200062
Author(s):
HUANG Danhua1WANG Su2
1. Library, East China University of Political Science and Law, Shanghai 200042,China 2. Computer Center, East China Normal University, Shanghai 200062,China
关键词:
货位分配COI分类存放粒子群算法人工蜂群算法
Keywords:
storage allocationCOIclass-based storageparticle swarm optimizationartificial bee colony
分类号:
TP391
DOI:
10.3969/j.issn.1009-671X.2012.201306013
文献标志码:
A
摘要:
基于COI分类存放的思想,同时考虑到货位分配问题中存取开销和占地花费的平衡,提出了一种混合粒子群算法以解决仓库货位优化分配问题.建立货位分配模型,并引入了货物的COI值对货物进行重新分类.将粒子群算法同人工蜂群算法相结合,通过优化COI值从而对货位进行优化分配.最后,进行实验分析并证明了混合粒子群算法的正确性,可有效地应用分类存放策对货位进行优化分配,减少货位数和存货代价.
Abstract:
Considering both of order-picking cost and storage-space cost, a hybrid particle swarm optimization algorithm is presented to solve the storage allocation optimization problem based on the COI warehouse storage policy. The storage allocation model is described and the concept of COI is introduced to reclassify the products and dispatch each of them to the most appropriate storage. The hybrid PSO algorithm combined PSO and artificial bee colony algorithm to get the best COI value so that it can get the best storage allocation resolution. Simulations Verify the hybrid PSO algorithm. The hybrid PSO algorithm can effectively employ COI Warehouse Storage Policy to optimize storage allocation and reduce both amount of storage allocation and cost.

参考文献/References:

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[2]MUPPANI M V R, ADIL G K. Efficient formation of storage classes for warehouse storage location assignment: a simulated annealing approach[J]. Omega, 2008, 36: 609-618.
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备注/Memo

备注/Memo:
收稿日期:2013-06-09.     网络出版日期:2013-07-04.
基金项目:上海市自然科学基金资助项目(10ZR1410400).
作者简介:黄丹华(1960-),女,工程师,主要研究方向:计算机应用技术、信息系统.E-mail:huangdanhua@ecupl.edu.cn.
更新日期/Last Update: 2013-09-30