.png){kind=icon}
返回
Agent-based flow-shop modelling in dynamic environment
.png){kind=icon}
PRE
AI
DOI：10.1080/09537287.2013.782946.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This article studies a multiple-objective flow-shop modelling and scheduling problem by multi-agent system (MAS) in a production context characterized by diversified, high-volume production mix. The analysed flow shop is characterised by multi-machine workstations, transfer batches, sequence-dependent setup times and possible re-entrant jobs. The agent-based model is structured from the current flow-shop configuration, defining the main entities and related events to realize the most possible flexible model. After a description of entities and their states, the agent framework with state diagrams is implemented through Jade platform. The system is provided with a simulation-based environment to test it in two main production scenarios including re-entrant jobs and failures. A coordination mechanism between agents and a dedicated scheduling algorithm managed by the MAS allowed to front this kind of events optimising concurrent objectives like work in process, Makespan and buffer queues.
Keyword:
dynamic flow shop
multi-agent system
re-entrant jobs
scheduling
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
P
IF:
5.4
论文数:
2.6K
被引数:
8.1K
机构
引用论文
.png){kind=icon}
分享收藏分享收藏
分享收藏分享收藏
查看更多内容