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A Sequence Planning Approach of Models for Sequencing Mixed-Model Assembly Lines

机译:混合模型装配线排序的模型序列计划方法

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Sequence planning of models for a mixed-model assembly line is crucial for the line efficiency. This paper formalized this model sequencing problem based on minimizing the total cost of idle time and overtime. An adapted Particle Swarm Optimization (PSO) algorithm was proposed to optimize the problem. To avoid early convergence of the particles, an immunity mechanism was introduced into the algorithm. The particle was replaced in time to keep the diversity according to the particle affinity and consistency, and so to avoid being trapped into local optimum. Furthermore, the solutions yielded by these approaches were compared to the traditional PSO algorithm, and the results showed that the method is perfect for sequence planning of mixed-model assembly lines.
机译:混合模型装配线的模型顺序计划对于生产线效率至关重要。本文在最小化空闲时间和加班总成本的基础上,对该模型排序问题进行形式化。提出了一种改进的粒子群算法(PSO)对问题进行优化。为了避免粒子的早期收敛,将免疫机制引入了算法。及时更换颗粒,以根据颗粒的亲和力和一致性保持多样性,从而避免陷入局部最优状态。此外,将这些方法产生的解决方案与传统的PSO算法进行了比较,结果表明该方法非常适合混合模型装配线的序列计划。

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