A simulated annealing algorithm for multi-manned assembly line balancing problem

Assembly line balancing problems with multi-manned workstations usually occur in plants producing high volume products (e.g. automotive industry) in which the size of the product is reasonably large to utilize the multi-manned assembly line configuration. In these kinds of assembly lines, usually there are multi-manned workstations where a group of workers simultaneously performs different operations on the same individual product. However, owing to the high computational complexity, it is quite difficult to achieve an optimal solution to the balancing problem of multi-manned assembly lines with traditional optimization approaches. In this study, a simulated annealing heuristic is proposed for solving assembly line balancing problems with multi-manned workstations. The line efficiency, line length and the smoothness index are considered as the performance criteria. The proposed algorithm is illustrated with a numerical example problem, and its performance is tested on a set of test problems taken from literature. The performance of the proposed algorithm is compared to the existing approaches. Results show that the proposed algorithm performs well.