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Model and migrating birds optimization algorithm for two-sided assembly line worker assignment and balancing problem

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journal contribution
posted on 20.03.2019, 12:20 by MN Janardhanan, Z Li, P Nielsen
Worker assignment is a relatively new problem in assembly lines that typically is encountered in situations in which the workforce is heterogeneous. The optimal assignment of a heterogeneous workforce is known as the assembly line worker assignment and balancing problem (ALWABP). This problem is different from the well-known simple assembly line balancing problem concerning the task execution times, and it varies according to the assigned worker. Minimal work has been reported in worker assignment in two-sided assembly lines. This research studies worker assignment and line balancing in two-sided assembly lines with an objective of minimizing the cycle time (TALWABP). A mixed-integer programming model is developed, and CPLEX solver is used to solve the small-size problems. An improved migrating birds optimization algorithm is employed to deal with the large-size problems due to the NP-hard nature of the problem. The proposed algorithm utilizes a restart mechanism to avoid being trapped in the local optima. The solutions obtained using the proposed algorithms are compared with well-known metaheuristic algorithms such as artificial bee colony and simulated annealing. Comparative study and statistical analysis indicate that the proposed algorithm can achieve the optimal solutions for small-size problems, and it shows superior performance over benchmark algorithms for large-size problems.

Funding

This research is partially supported by National Science Foundation of China under grant 61803287 and China Postdoctoral Science Foundation under grant 2018M642928.

History

Citation

Soft Computing, 2018, pp. 1-14

Author affiliation

/Organisation/COLLEGE OF SCIENCE AND ENGINEERING/Department of Engineering

Version

AM (Accepted Manuscript)

Published in

Soft Computing

Publisher

Springer (part of Springer Nature): Springer Open Choice Hybrid Journals for Springer Berlin Heidelberg

issn

1432-7643

eissn

1433-7479

Copyright date

2018

Publisher version

https://link.springer.com/article/10.1007/s00500-018-03684-8

Notes

The file associated with this record is under embargo until 12 months after publication, in accordance with the publisher's self-archiving policy. The full text may be available through the publisher links provided above.

Language

en

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