• 主题
高级搜索  >
历史搜索 清空历史
首页> 美国卫生研究院文献>The Scientific World Journal >Order Batching in Warehouses by Minimizing Total Tardiness: A Hybrid Approach of Weighted Association Rule Mining and Genetic Algorithms
【2h】

Order Batching in Warehouses by Minimizing Total Tardiness: A Hybrid Approach of Weighted Association Rule Mining and Genetic Algorithms

机译：通过最大程度地减少总拖延来进行仓库中的订单批处理：加权关联规则挖掘和遗传算法的混合方法

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务，本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文，但由于OA文献来源多样且变更频繁，仍可能出现获取不到、文献不完整或与标题不符等情况，如果获取不到我们将提供退款服务。请知悉。
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

One of the cost-intensive issues in managing warehouses is the order picking problem which deals with the retrieval of items from their storage locations in order to meet customer requests. Many solution approaches have been proposed in order to minimize traveling distance in the process of order picking. However, in practice, customer orders have to be completed by certain due dates in order to avoid tardiness which is neglected in most of the related scientific papers. Consequently, we proposed a novel solution approach in order to minimize tardiness which consists of four phases. First of all, weighted association rule mining has been used to calculate associations between orders with respect to their due date. Next, a batching model based on binary integer programming has been formulated to maximize the associations between orders within each batch. Subsequently, the order picking phase will come up which used a Genetic Algorithm integrated with the Traveling Salesman Problem in order to identify the most suitable travel path. Finally, the Genetic Algorithm has been applied for sequencing the constructed batches in order to minimize tardiness. Illustrative examples and comparisons are presented to demonstrate the proficiency and solution quality of the proposed approach.
机译：管理仓库中成本密集的问题之一是订单拣选问题，该问题涉及从其存储位置取回物品以满足客户的要求。为了使订单拣选过程中的行驶距离最小化，已经提出了许多解决方案。但是，实际上，必须避免在某些截止日期之前完成客户订单，以免拖延，而拖延是大多数相关科学论文中所忽略的。因此，我们提出了一种新颖的解决方案方法，以使拖延时间最小化，该方法包括四个阶段。首先，已使用加权关联规则挖掘来计算订单之间相对于其到期日期的关联。接下来，已经制定了基于二进制整数编程的批处理模型，以使每个批中的订单之间的关联最大化。随后，将出现订单拣选阶段，该阶段将遗传算法与Traveling Salesman问题集成在一起，以确定最合适的行进路径。最后，遗传算法已用于对构建的批次进行测序，以最大程度地减少拖延。给出了说明性示例和比较，以证明所提出方法的熟练程度和解决方案质量。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

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