TY - JOUR
T1 - Metaheuristic algorithms for balancing robotic assembly lines with sequence-dependent robot setup times
AU - Janardhanan, Mukund Nilakantan
AU - Li, Zixiang
AU - Bocewicz, Grzegorz
AU - Banaszak, Zbigniew
AU - Nielsen, Peter
PY - 2019/1/1
Y1 - 2019/1/1
N2 - Industries are incorporating robots into assembly lines due to their greater flexibility and reduced costs. Most of the reported studies did not consider scheduling of tasks or the sequence-dependent setup times in an assembly line, which cannot be neglected in a real-world scenario. This paper presents a study on robotic assembly line balancing, with the aim of minimizing cycle time by considering sequence-dependent setup times. A mathematical model for the problem is formulated and CPLEX solver is utilized to solve small-sized problems. A recently developed metaheuristic Migrating Birds Optimization (MBO) algorithm and set of metaheuristics have been implemented to solve the problem. Three different scenarios are tested (with no setup time, and low and high setup times). The comparative experimental study demonstrates that the performance of the MBO algorithm is superior for the tested datasets. The outcomes of this study can help production managers improve their production system in order to perform the assembly tasks with high levels of efficiency and quality.
AB - Industries are incorporating robots into assembly lines due to their greater flexibility and reduced costs. Most of the reported studies did not consider scheduling of tasks or the sequence-dependent setup times in an assembly line, which cannot be neglected in a real-world scenario. This paper presents a study on robotic assembly line balancing, with the aim of minimizing cycle time by considering sequence-dependent setup times. A mathematical model for the problem is formulated and CPLEX solver is utilized to solve small-sized problems. A recently developed metaheuristic Migrating Birds Optimization (MBO) algorithm and set of metaheuristics have been implemented to solve the problem. Three different scenarios are tested (with no setup time, and low and high setup times). The comparative experimental study demonstrates that the performance of the MBO algorithm is superior for the tested datasets. The outcomes of this study can help production managers improve their production system in order to perform the assembly tasks with high levels of efficiency and quality.
KW - Assembly line balancing
KW - Metaheuristics
KW - Robotic assembly line
KW - Sequence-dependent setup times
UR - http://www.scopus.com/inward/record.url?scp=85053076420&partnerID=8YFLogxK
U2 - 10.1016/j.apm.2018.08.016
DO - 10.1016/j.apm.2018.08.016
M3 - Journal article
AN - SCOPUS:85053076420
SN - 0307-904X
VL - 65
SP - 256
EP - 270
JO - Applied Mathematical Modelling
JF - Applied Mathematical Modelling
ER -