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Mathematical model and metaheuristics for simultaneous balancing and sequencing of a robotic mixed-model assembly line

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journal contribution
posted on 26.03.2020, 11:04 by Zixiang Li, Mukund N. Janardhanan, Qiuhua Tang, Peter Nielsen
This article presents the first method to simultaneously balance and sequence robotic mixed-model assembly lines (RMALB/S), which involves three sub-problems: task assignment, model sequencing and robot allocation. A new mixed-integer programming model is developed to minimize makespan and, using CPLEX solver, small-size problems are solved for optimality. Two metaheuristics, the restarted simulated annealing algorithm and co-evolutionary algorithm, are developed and improved to address this NP-hard problem. The restarted simulated annealing method replaces the current temperature with a new temperature to restart the search process. The co-evolutionary method uses a restart mechanism to generate a new population by modifying several vectors simultaneously. The proposed algorithms are tested on a set of benchmark problems and compared with five other high-performing metaheuristics. The proposed algorithms outperform their original editions and the benchmarked methods. The proposed algorithms are able to solve the balancing and sequencing problem of a robotic mixed-model assembly line effectively and efficiently.

History

Citation

Engineering Optimization, 2018 VOL. 50, NO. 5, 877–893

Author affiliation

Department of Engineering

Version

AM (Accepted Manuscript)

Published in

Engineering Optimization

Volume

50

Issue

5

Pagination

877 - 893

Publisher

Informa UK Limited

issn

0305-215X

eissn

1029-0273

Acceptance date

01/07/2017

Copyright date

2017

Available date

24/07/2017

Publisher version

https://www.tandfonline.com/doi/full/10.1080/0305215X.2017.1351963

Language

en