caa a22 4500 60615910X CHVBK 20210128100623.0 cr unu---uuuuu 210128e20150801xx s 000 0 eng 10.1007/s00521-014-1811-x doi (NATIONALLICENCE)springer-10.1007/s00521-014-1811-x Bio-inspired search algorithms to solve robotic assembly line balancing problems [Elektronische Daten] [J. Mukund Nilakantan, S. Ponnambalam, N. Jawahar, G. Kanagaraj] Robots are employed in assembly lines to increase the productivity. The objective of robotic assembly line balancing (rALB) problem is to balance the assembly line, by allocating equal amount of tasks to the workstations on the line while assigning the most efficient robot to perform the assembly task at the workstation. In this paper, bio-inspired search algorithms, viz. particle swarm optimization (PSO) algorithm and a hybrid cuckoo search and particle swarm optimization (CS-PSO), are proposed to balance the robotic assembly line with the objective of minimizing the cycle time. The performance of the proposed PSO and hybrid CS-PSO is evaluated using the 32 benchmark problems available in the literature. The simulation results show that both PSO and hybrid CS-PSO are capable of providing solutions within the upper bound obtained by hybrid GA, the only metaheuristic reported so far for rALB in the literature and comparable to the solutions obtained by IBM CPLEX Optimization solver. It is also observed that hybrid CS-PSO is performing better than PSO in terms of cycle time. The Natural Computing Applications Forum, 2014 Robotic assembly line balancing nationallicence Particle swarm optimization nationallicence Cuckoo search nationallicence Local search nationallicence Mukund Nilakantan J. Advanced Engineering Platform and School of Engineering, Monash University Malaysia, 46150, Bandar Sunway, Malaysia aut Ponnambalam S. Advanced Engineering Platform and School of Engineering, Monash University Malaysia, 46150, Bandar Sunway, Malaysia aut Jawahar N. Department of Mechanical Engineering, Thiagarajar College of Engineering, Madurai, India aut Kanagaraj G. Department of Mechanical Engineering, Thiagarajar College of Engineering, Madurai, India aut Neural Computing and Applications Springer London 26/6(2015-08-01), 1379-1393 0941-0643 26:6<1379 2015 26 521 https://doi.org/10.1007/s00521-014-1811-x text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00521-014-1811-x text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Mukund Nilakantan J. Advanced Engineering Platform and School of Engineering, Monash University Malaysia, 46150, Bandar Sunway, Malaysia aut NATIONALLICENCE 700 1- Ponnambalam S. Advanced Engineering Platform and School of Engineering, Monash University Malaysia, 46150, Bandar Sunway, Malaysia aut NATIONALLICENCE 700 1- Jawahar N. Department of Mechanical Engineering, Thiagarajar College of Engineering, Madurai, India aut NATIONALLICENCE 700 1- Kanagaraj G. Department of Mechanical Engineering, Thiagarajar College of Engineering, Madurai, India aut NATIONALLICENCE 773 0- Neural Computing and Applications Springer London 26/6(2015-08-01), 1379-1393 0941-0643 26:6<1379 2015 26 521