Scheduling parallel mixed-model assembly lines with cross-line item transfers

Yossi Bukchin and Eugene Khmelnitsky

International Journal of Production Research, 2025, vol. 63, issue 21, 7980-7997

Abstract: This paper investigates a system of parallel, identical assembly lines, where items can either remain on the same line or transfer to another line. The objective is to minimise the makespan or a cost function. First, the system is analysed under deterministic assumptions using a mixed-integer linear programming (MILP) model. The effects of transfers and in-transfer storage on the makespan are examined. Then, a Markov Decision Process (MDP) solution is introduced for stochastic conditions, where item arrivals and process times are uncertain. An MDP-based heuristic is developed to handle large-scale systems with many stages. Its performance, which considers both the makespan and transfer costs, is compared with a simplified myopic method. Results indicate that the makespan increases with the process time variability by 13% in the MILP model and 16% in the MDP solution. Transfers improve performance, reducing makespan by an average of 10%, both by the MILP and the MDP. In the deterministic case, both transfers and in-transfer storage lead to notable improvements, with makespan reductions of 5% to 13%. In the stochastic case, the number of stages and the transfer cost parameter affect the choice of the best policy.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2025.2509151 (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:63:y:2025:i:21:p:7980-7997

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

DOI: 10.1080/00207543.2025.2509151

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 ().