Abstract
Assembly line balancing is the problem of assigning tasks to workstations by optimizing a performance measure while satisfying precedence relations between tasks and cycle time restrictions. Many exact, heuristic and metaheuristic approaches have been proposed for solving simple straight and U-shaped assembly line balancing problems. In this study, a relatively new optimization algorithm, Bacterial Foraging Optimization Algorithm (BFOA), based heuristic approach is proposed for solving simple straight and U-shaped assembly line balancing problems. The performance of the proposed algorithm is evaluated using a well-known data set taken from the literature in which the number of tasks varies between 7 and 111, and results are also compared with both an ant-colony-optimization-based heuristic approach and a genetic-algorithm-based heuristic approach. The proposed algorithm provided optimal solutions for 123 out of 128 (96.1 %) test problems in seconds and is proven to be promising.
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