TY - GEN
T1 - Artificial bee colony algorithms for two-sided assembly line worker assignment and balancing problem
AU - Janardhanan, Mukund Nilakantan
AU - Li, Zixiang
AU - Nielsen, Peter
AU - Tang, Qiuhua
PY - 2018
Y1 - 2018
N2 - Worker assignment is a new type of problem in assembly line balancing problems, which typically occurs in sheltered work centers for the disabled. However, only a few contributions consider worker assignment in a two-sided assembly line. This research presents three variants of artificial bee colony algorithm to solve worker assignment and line balancing in two-sided assembly lines. The utilization of meta-heuristics is motivated by the NP-hard nature of the problem and the chosen methods utilize different operators for onlooker phase and scout phase. The proposed algorithms are tested on 156 cases generated from benchmark problems. A comparative study is conducted on the results obtained from the three proposed variants and other well-known metaheuristic algorithms, such as simulated annealing, particle swarm optimization and genetic algorithm. The computational study demonstrates that the proposed variants produce more promising results and are able to solve this new problem effectively in an acceptable computational time.
AB - Worker assignment is a new type of problem in assembly line balancing problems, which typically occurs in sheltered work centers for the disabled. However, only a few contributions consider worker assignment in a two-sided assembly line. This research presents three variants of artificial bee colony algorithm to solve worker assignment and line balancing in two-sided assembly lines. The utilization of meta-heuristics is motivated by the NP-hard nature of the problem and the chosen methods utilize different operators for onlooker phase and scout phase. The proposed algorithms are tested on 156 cases generated from benchmark problems. A comparative study is conducted on the results obtained from the three proposed variants and other well-known metaheuristic algorithms, such as simulated annealing, particle swarm optimization and genetic algorithm. The computational study demonstrates that the proposed variants produce more promising results and are able to solve this new problem effectively in an acceptable computational time.
KW - Artificial bee colony
KW - Assembly line balancing
KW - Metaheuristics
KW - Two-sided assembly line
KW - Worker assignment
UR - http://www.scopus.com/inward/record.url?scp=85022190420&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-62410-5_2
DO - 10.1007/978-3-319-62410-5_2
M3 - Article in proceeding
AN - SCOPUS:85022190420
SN - 9783319624099
T3 - Advances in Intelligent Systems and Computing
SP - 11
EP - 18
BT - Distributed Computing and Artificial Intelligence, 14th International Conference
PB - Springer
T2 - 14th International Symposium on Distributed Computing and Artificial Intelligence, DCAI 2017
Y2 - 21 June 2017 through 23 June 2017
ER -