Capacity smoothing and job shop scheduling with backlog carryover and job prioritisation: a case study from the carbon graphite processing industry

Michael Jahr and Sebastian Fußel

International Journal of Operational Research, 2024, vol. 50, issue 3, 316-331

Abstract: In this paper, we consider the job shop scheduling problem (JSSP) in single-stage production with n-jobs and m-parallel unrelated machines. We present a specific multi-objective nonlinear binary optimisation model for a real-life case study from the carbon graphite processing industry. In particular, we develop a trade-off objective function with job prioritisation subject to capacity constraints and backlog carryover, implemented in the GAMS standard optimisation software package and solved with the BARON solver. The approach is compared to an adjusted Moore-Hodgson heuristics and the company's existing first come first serve-based procedure. The application of the model on a realistic data set and the analysis of the results validate that the presented approach is efficient.

Keywords: job shop scheduling; binary programming; capacity smoothing; job prioritisation. (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=139266 (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:ids:ijores:v:50:y:2024:i:3:p:316-331

Access Statistics for this article

More articles in International Journal of Operational Research from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().