An efficient migrating birds optimization algorithm with idle time reduction for Type-I multi-manned assembly line balancing problem

Multi-manned assembly line, which is broadly utilized to assemble high volume products such as automobiles and trucks, allows a group of workers different tasks simultaneously in multi-manned workstation. This additional characteristic parallel operators increases the complexity traditional NP-hard line balancing problem. Hence, this paper formulates Type-I problem minimize total number workstations operators, develops an efficient migrating birds optimization algorithm embedded into idle time reduction method. In algorithm, new decoding mechanism proposed reduces sequence-dependent by some task assignment rules; three effective neighborhoods are developed make refinement existing solutions bird improvement phases; temperature acceptance competitive employed avoid being trapped local optimum. Comparison experiments suggest that improvements outperforms compared algorithms.