机器人人工拣选环境下混流装配线齐套物料配送优化

Optimization of kitting material distribution of mixed-model assembly line under robot-operator picking environment

为了提高汽车制造企业配送的智能化水平、解决混流装配线齐套物料人工拣选效率低、成本高的问题,引入基于齐套物料配送策略的机器人人工拣选模式,通过优化自动拣选机器人、工人的配置数量及配送周期,使包含机器人使用成本、劳动力成本和在制品库存成本在内的总成本最小。为求解该配送优化问题,提出了改进量子蚁群算法,利用量子比特的叠加性增加种群多样性,避免算法陷入局部最优,同时设计了改进量子旋转门更新机制和基于差分进化操作的非最优个体优化策略,提高了算法收敛速度和寻优质量。最后,通过算例分析验证了模型的正确性与算法的有效性,并分析了拣选批量对总成本的影响。

To improve the intelligent level of distribution in automobile manufacturing enterprises and solve the problems of low efficiency and high cost of manual picking,a robot-operator picking mode based on kitting policy was introduced.The total costs,including robot usage,labor and WIP inventory costs were minimized by optimizing the number of labors,robots and tour period.To solve this optimization problem,an improved quantum-inspired ant colony optimization algorithm was constructed.The superposition of quantum bits was used to increase the population diversity and avoid the algorithm falling into local optimization.An improved quantum rotation gate update mechanism and a non-optimal individual optimization strategy based on differential evolution operation were designed to improve the convergence speed and quality of the algorithm.Finally,numerical experiments were presented to demonstrate the correctness of the model and the effectiveness of the algorithm,and the influence of picking batch size on cost was analyzed.