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针对产品结构特征建立几何约束矩阵,以最大化满足几何约束条件装配次数和最小化装配方向改变次数为目标,研究产品装配序列优化问题.利用值变换的粒子位置和速度更新规则,基于具有随机性启发式算法产生初始种群,提出一种带有深度邻域搜索改进策略的粒子群算法解决装配序列问题.通过装配实例验证了所提出算法的性能并对装配序列质量进行了评价,所得结果表明了该算法在解决装配序列优化问题上的有效性与稳定性.
The geometric constraint matrix is established according to the structural features of the product, and the optimization of the assembly sequence is studied with the objective of maximizing the number of assembly times and minimizing the number of changes in the assembly direction. The particle location and velocity update rules based on the value transformation are based on the randomness A heuristic algorithm is used to generate the initial population and a particle swarm optimization algorithm with depth neighborhood search is proposed to solve the assembly sequence problem.The performance of the proposed algorithm is verified by the assembly example and the quality of the assembly sequence is evaluated.The results show that The algorithm is effective and stable in solving the optimization of assembly sequence.