知识发现的补偿模糊逻辑应用于实时订单批处理的仓库拣货问题

L. Cruz-Reyes, R. Espín-Andrade, Fernando López Irrarragorri, César Medina-Trejo, José Tristán, Daniel Martínez-Vega, Carlos E. Peralta
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引用次数: 6

摘要

订单挑选是仓库中的一项活动,由一个团队执行,在那里准备客户订单。这也是公司中物流成本最高的活动。在本章中,提出了一个改进仓库拣货流程的建议。订单挑选继续吸引负责优化公司流程以最小化成本的人的注意。有几种方法的订单拣选,如离散拣选,批量拣选,和区域拣选。本研究的目的主要是为了减少分批拣货时间,以达到改善服务的目的。在这一章中,提出了补偿模糊逻辑(CFL)的应用,它是经典逻辑的一个分支,并讨论了利用补偿模糊规则对传入订单进行分类,从而实现实时订单批量(动态批处理)的可能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Use of Compensatory Fuzzy Logic for Knowledge Discovery Applied to the Warehouse Order Picking Problem for Real-Time Order Batching
Order picking is an activity in a warehouse, carried out by a team, where customer orders are prepared. It is also the activity with the highest logistic costs in a company. In this chapter, a proposal is presented aimed at improving the order picking process in a warehouse. Order picking continues to attract the attention of people in charge of optimizing processes in a company for minimizing costs. There are several approaches to order picking such as discrete picking, batch picking, and zone picking. The purpose of this study is mainly oriented toward the reduction of batch picking times to achieve an improvement in the service. In this chapter is proposed the application of compensatory fuzzy logic (CFL), which is a branch of classical logic and is also discussed the possibility of making real-time order batches (dynamic batching) by using compensatory fuzzy rules for the classification of incoming orders.
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