Model and metaheuristics for robotic two-sided assembly line balancing problems with setup times

Two-sided robotic assembly lines are employed to assemble large-sized high-volume products, where robots are allocated to the workstations to perform the tasks and human workers are replaced for achieving lower cost and greater flexibility in production. In the two-sided robotic assembly lines, setu...

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Main Authors: Li, Zixiang, Janardhanan, Mukund Nilakantan, Tang, Qiuhua, Ponnambalam, S. G.
Format: Article
Language:en
Published: Elsevier B.V. 2019
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/26103/1/Model%20and%20metaheuristics%20for%20robotic%20two-sided%20assembly%20.pdf
http://umpir.ump.edu.my/id/eprint/26103/
https://doi.org/10.1016/j.swevo.2019.100567
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author Li, Zixiang
Janardhanan, Mukund Nilakantan
Tang, Qiuhua
Ponnambalam, S. G.
author_facet Li, Zixiang
Janardhanan, Mukund Nilakantan
Tang, Qiuhua
Ponnambalam, S. G.
author_sort Li, Zixiang
building UMPSA Library
collection Institutional Repository
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
continent Asia
country Malaysia
description Two-sided robotic assembly lines are employed to assemble large-sized high-volume products, where robots are allocated to the workstations to perform the tasks and human workers are replaced for achieving lower cost and greater flexibility in production. In the two-sided robotic assembly lines, setup times are unavoidable and it has been ignored in most of the reported works. There has been limited attention on this till date. This paper focusses on the robotic two-sided assembly line with consideration of sequence-dependent setup times and robot setup times. A new mixed integer linear programming model is developed with the objective of optimizing the cycle time. Due to the NP-hard nature of the considered problem, this paper proposes a set of metaheuristics to solve this considered problem, where two main scenarios with low and high setup time’s variability are considered. Computational results verify that this new model is capable to achieve the optimal solutions for small-size instances whereas the simple adoption of the published mathematical model might produce wrong solutions for the considered problem. A comprehensive study with 13 algorithms demonstrates that the two variants of artificial bee colony algorithm and migrating bird optimization algorithm are capable to achieve the optimality for small-size instances and to obtain promising results for large-size instances.
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spelling my.ump.umpir.261032019-10-16T08:08:59Z http://umpir.ump.edu.my/id/eprint/26103/ Model and metaheuristics for robotic two-sided assembly line balancing problems with setup times Li, Zixiang Janardhanan, Mukund Nilakantan Tang, Qiuhua Ponnambalam, S. G. QA75 Electronic computers. Computer science QC Physics TJ Mechanical engineering and machinery TS Manufactures Two-sided robotic assembly lines are employed to assemble large-sized high-volume products, where robots are allocated to the workstations to perform the tasks and human workers are replaced for achieving lower cost and greater flexibility in production. In the two-sided robotic assembly lines, setup times are unavoidable and it has been ignored in most of the reported works. There has been limited attention on this till date. This paper focusses on the robotic two-sided assembly line with consideration of sequence-dependent setup times and robot setup times. A new mixed integer linear programming model is developed with the objective of optimizing the cycle time. Due to the NP-hard nature of the considered problem, this paper proposes a set of metaheuristics to solve this considered problem, where two main scenarios with low and high setup time’s variability are considered. Computational results verify that this new model is capable to achieve the optimal solutions for small-size instances whereas the simple adoption of the published mathematical model might produce wrong solutions for the considered problem. A comprehensive study with 13 algorithms demonstrates that the two variants of artificial bee colony algorithm and migrating bird optimization algorithm are capable to achieve the optimality for small-size instances and to obtain promising results for large-size instances. Elsevier B.V. 2019-08-23 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/26103/1/Model%20and%20metaheuristics%20for%20robotic%20two-sided%20assembly%20.pdf Li, Zixiang and Janardhanan, Mukund Nilakantan and Tang, Qiuhua and Ponnambalam, S. G. (2019) Model and metaheuristics for robotic two-sided assembly line balancing problems with setup times. Swarm and Evolutionary Computation, 50 (100567). ISSN 2210-6502. (Published) https://doi.org/10.1016/j.swevo.2019.100567 https://doi.org/10.1016/j.swevo.2019.100567
spellingShingle QA75 Electronic computers. Computer science
QC Physics
TJ Mechanical engineering and machinery
TS Manufactures
Li, Zixiang
Janardhanan, Mukund Nilakantan
Tang, Qiuhua
Ponnambalam, S. G.
Model and metaheuristics for robotic two-sided assembly line balancing problems with setup times
title Model and metaheuristics for robotic two-sided assembly line balancing problems with setup times
title_full Model and metaheuristics for robotic two-sided assembly line balancing problems with setup times
title_fullStr Model and metaheuristics for robotic two-sided assembly line balancing problems with setup times
title_full_unstemmed Model and metaheuristics for robotic two-sided assembly line balancing problems with setup times
title_short Model and metaheuristics for robotic two-sided assembly line balancing problems with setup times
title_sort model and metaheuristics for robotic two-sided assembly line balancing problems with setup times
topic QA75 Electronic computers. Computer science
QC Physics
TJ Mechanical engineering and machinery
TS Manufactures
url http://umpir.ump.edu.my/id/eprint/26103/1/Model%20and%20metaheuristics%20for%20robotic%20two-sided%20assembly%20.pdf
http://umpir.ump.edu.my/id/eprint/26103/
https://doi.org/10.1016/j.swevo.2019.100567
https://doi.org/10.1016/j.swevo.2019.100567
url_provider http://umpir.ump.edu.my/