Combinatorial Benders decomposition for melted material blending systems considering transportation and scheduling

Myungeun Eom and Byung-In Kim

International Journal of Production Research, 2023, vol. 61, issue 10, 3481-3503

Abstract: We study an integrated optimisation problem with blending, scheduling, and routing components for a melted material blending production system. The problem is formulated as a mixed-integer linear programming model that considers the blending machine environment, due dates, target amounts, required chemical compositions of the products, and ready times of the materials in containers. This model aimed to determine the container pairings, blending plants for container pairs, and schedules for blending operations while minimising the total end time of material usage, total penalty for violating component specifications, and employee workload. Further, we propose a three-stage approach that involves solving a relaxed problem and then resolving the problem with fixed variables. We developed a combinatorial Benders decomposition algorithm with a minimal infeasible subsystem identification algorithm for the blending scheduling problem. The experimental results indicate that the proposed method can find high-quality solutions within a reasonable amount of time.

Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2022.2086084 (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:61:y:2023:i:10:p:3481-3503

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

DOI: 10.1080/00207543.2022.2086084

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 ().