决策支持系统
计算机科学
全渠道
供应链
仓库
数据仓库
多样性(控制论)
决策分析
服务(商务)
政府(语言学)
过程管理
运筹学
知识管理
业务
数据库
营销
工程类
经济
数据挖掘
万维网
人工智能
数理经济学
哲学
语言学
作者
Tania Binos,Arthur Adamopoulos,Vince Bruno
标识
DOI:10.1142/s0219622020300013
摘要
The increase in e-commerce and omnichannel commerce is having a significant impact on the supply chain sector and its warehouses. Fluctuations in demand and priorities, the requirement for value-added service, government regulations and other factors put pressure on the operational decision makers on the warehouse floor and the systems that support them. The increasing complexity of daily warehouse operations means that decision support systems will need to become more sophisticated and intelligent to assist decision makers in real-time. The aim of this literature review is to investigate how decision support in warehousing and distribution operations is examined in the research literature. The objective of this review is to understand how this decision support research can assist operational decision makers to manage and complete the daily volume of work through the warehouse. Fifty-one articles were obtained by the literature search. Articles were categorized by type of warehouse, decision support target, operational task and problem type, research article methodology, architecture and technology. Decision support is examined in almost all areas of warehousing operations with the use of a variety of methods and technologies within the research literature. Most “daily warehouse operational” decision support deals with expertise transfer and reacting to real-time events. This paper highlights the lack of research into human–machine collaboration in adaptive decision support systems to assist warehouse operational decision makers.
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