Trigonometric-based mechanisms hybridized African vulture optimization algorithm for multi-manned disassembly line balancing involving worker heterogeneity and collaboration

Yufan Huang () and Binghai Zhou ()
Additional contact information
Yufan Huang: Tongji University
Binghai Zhou: Tongji University

Journal of Intelligent Manufacturing, 2025, vol. 36, issue 6, No 23, 4143-4199

Abstract: Abstract The rapid replacement of large-scale end-of-life (EOL) heavy machineries like automobiles, aircrafts and industrial robots necessitates efficient resource recovery to promote sustainable and eco-friendly manufacturing. This study therefore focuses on multi-manned disassembly lines in recycling large-scale products, bridging the gap between theory and practice. We introduce complex, safety-sensitive tasks that require collaborative efforts of multiple workers in the Multi-Manned Disassembly Line Balancing Problem (MMDLBP) for the first time. We also consider worker heterogeneity due to varying training and skills, as manual stations are inherently worker-dependent in nature. To address this Multi-Manned Disassembly Line Balancing Problem with Worker Heterogeneity and Collaboration (MMDLBP-HC), we establish a mixed-integer programming model to minimize cycle time and labor cost simultaneously. Given its NP-hard nature, we develop a Multi-Mechanism-Enhanced Bi-Objective African Vultures Optimization Algorithm (MBAVOA). It employs specified encoding with numerical branching, precedence-priority concurrent decoding, and selective opposition-based learning. We also combine trigonometric-based mechanisms with the African vulture optimization algorithm (AVOA) to enhance exploration. Additionally, adaptive neighborhood search mechanisms are tailored for inter-individual information exchange. Numerical experiments compare MBAVOA to four meta-heuristics and an exact algorithm. The results demonstrate the model accuracy and the effectiveness of the encoding and decoding mechanisms, while MBAVOA outperforms benchmark algorithms significantly. Finally, we offer managerial applications to guide practitioners in balancing plan formation and training program design.

Keywords: Multi-manned disassembly line balancing; Worker heterogeneity; Worker collaboration; African vulture optimization algorithm; Trigonometric-based mechanisms (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10845-024-02443-x Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:joinma:v:36:y:2025:i:6:d:10.1007_s10845-024-02443-x

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10845

DOI: 10.1007/s10845-024-02443-x

Access Statistics for this article

Journal of Intelligent Manufacturing is currently edited by Andrew Kusiak

More articles in Journal of Intelligent Manufacturing from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().