EconPapers    
Economics at your fingertips  
 

Multi-agent-based hierarchical collaborative scheduling in re-entrant manufacturing systems

Jie Zhang and Xiaoxi Wang

International Journal of Production Research, 2016, vol. 54, issue 23, 7043-7059

Abstract: Production scheduling problems in re-entrant manufacturing systems are complex due to their features of large-scale complexity, unbalanced workload and dynamic uncertainty. The aim of this paper is thus to develop an effective way of formulating production schedules for designing RMSs. First, a multi-agent-based hierarchical collaborative system consisting of a system layer, a machine layer, and a material handling device layer is developed to improve the efficiency of RMSs. The objective of the system layer is to maximise the total processing profit, and the objective of the machine layer is to determine the winning bid. Second, a contract net protocol scheduling algorithm is applied to solve capacity planning problems for key machine groups in the system layer. Third, a generalised partial global planning-contract net collaborative mechanism is adopted to allocate tasks to machines within each machine group in the machine layer. Finally, the performance of the proposed approach is validated through a case study, and the results demonstrate that the proposed approach outperforms the first-come first-serve rule in combination with the minimised batch size rule in terms of daily movement and machine utilisation.

Date: 2016
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2016.1194535 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tprsxx:v:54:y:2016:i:23:p:7043-7059

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20

DOI: 10.1080/00207543.2016.1194535

Access Statistics for this article

International Journal of Production Research is currently edited by Professor A. Dolgui

More articles in International Journal of Production Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:tprsxx:v:54:y:2016:i:23:p:7043-7059