Abstract
Abstract A PSO-GA-based method is proposed to improve the efficiency of complex product assembly sequence planning. We minimize total assembly time by optimizing the assembly sequence, considering the number of tool changes and assembly direction changes as evaluation criteria. A genetic algorithm (GA) is introduced into particle swarm optimization (PSO) to solve and verify assembly sequence planning. Finally, the effectiveness and rationality of the hybrid algorithm are verified by taking a certain type of gear pump as an example.
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