Priority rules-based algorithmic design on two-sided assembly line balancing

The two-sided assembly line becomes very popular in recent years. In this paper, a priority rules-based algorithmic design is developed for optimizing two-sided assembly line. Five elementary rules and 90 composite rules are tested on the benchmark data sets and their performance are provided. Two enumerative principles, which are specific to two-sided assembly lines are proposed to enhance the performance of the rules. Further, priority rules are embedded into a bounded dynamic programming framework to form a deterministic algorithm where the use of a bound can reduce the solution space as the algorithm is advanced stage-by-stage. These approaches offer distinct advantages over the methods proposed in the literature, such as less fine-tuning effort and more stable results. Computational results show that the novel algorithm can generate good solutions efficiently, especially in large sized problems.