首页> 外文期刊>International journal of wireless and mobile computing >Effective storage location assignment model based on a genetic simulation annealing algorithm
【24h】

Effective storage location assignment model based on a genetic simulation annealing algorithm

机译:基于遗传仿真退火算法的有效存储位置分配模型

获取原文
获取原文并翻译 | 示例
       

摘要

Automated warehouses have become the main application equipment in logistics due to their access automation and simple operation. In order to adapt to the increasingly rapid logistics speed, it is necessary to optimise the location assignment of items in the automated warehouse. Firstly, according to the characteristics of the automated warehouse operation environment, the storage location assignment optimisation model with the shortest time of items travelling the warehouse, the minimum distance between related items and the lowest orthocentre of the shelf is proposed. Then according to the characteristics of the optimisation model and the shortcomings of the traditional genetic algorithm (GA), the defects of the GA are improved and the fusion with the simulated annealing algorithm (SA) is completed, so as to form an improved genetic simulation annealing algorithm (SAGA) for the model. Finally, the effectiveness and superiority of the improved fusion algorithm are verified by comparing the SA, the SAGA and the improved SAGA.
机译:由于进入自动化和操作简单,自动化仓库已成为物流的主要应用设备。为了适应日益快速的物流速度,有必要优化自动仓库中项目的位置分配。首先,根据自动仓库运营环境的特点,存储位置分配优化模型具有最短的行进时间行驶仓库,相关项目之间的最小距离和架子的最低型架。然后根据优化模型的特性和传统遗传算法(GA)的缺点,改善了GA的缺陷,并且完成了模拟退火算法(SA)的融合,以形成改进的遗传模拟模型的退火算法(SAGA)。最后,通过比较SA,SAGA和改进的SAGA来验证改进的融合算法的有效性和优越性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号