采用遗传算法的混流装配线平衡多目标优化

Multi-objective optimization for mixed-model assembly line balancing problem based on GA

针对混流装配线操作人数已知、生产节拍待定情况下的平衡问题,研究了混流装配线第二类平衡问题的优化方法,以均衡各工作站的加权平均负荷、最小化生产节拍为优化目标,建立了求解加权平均负荷与生产节拍加权和的数学模型,并运用遗传算法对其进行求解。各优化目标数量级的统一,简化了算法求解过程,在保证解的有效性的同时提高了算法求解效率。算例分析验证了算法的有效性。

To minimize the cycle time of mixed-model assembly lines, a genetic algorithm based approach to the mixed-model assembly line balancing problem of type Ⅱ was studied,with the number of operators has been given. Balancing weighted average workload and minimum of the cycle time were proposed as the objectives of the mathematical programming model. A genetic algorithm was used to solve this model. By uniting the magnitude of the optimization objectives, the process of the genetic algorithm was simplified, and the efficiency of the algorithm was improved.