基于随机权重多目标遗传算法的多目标动态单元构建方法

Formation of Multi-Objective Dynamic Cells Using Random Weight Multi-Objective Genetic Algorithm

考虑多变的市场需求环境下单元生产系统在多个计划期具有多个目标的动态构建决策问题。通过对单元生产构建过程中的总费用、设备负载与能力之间最大偏差以及零部件跨单元移动的总次数3个目标进行权衡,建立了非线性多目标动态单元构建的数学模型。采用自适应小生境技术、惩罚技术、双轮盘赌法和精华选择策略,提出了基于精华保留策略的随机权重多目标遗传算法求解该组合优化问题。结合实例对模型和算法进行了仿真分析,结果显示了算法对解决多目标动态单元构建问题的有效性。

The problem of how to form dynamic cells based on changing production requirements with multiple planning horizons and multiple objectives was discussed. A nonlinear multi-objective mathematical model of dynamic cell formation was built by weighing the three objectives, including total cost in the process of cell manufacturing and formation, maximum deviation of workload from available capacities of machines, and total number of inter-cell moves. Using adaptive niche technique, penalty technique, double roulette wheel method, and reserving elite strategy, reserving elitebased random weight multi-objective genetic algorithm was designed for the complicated combination optimization model. The model and algorithm were analyzed by a numerical example. The computational results demonstrate that the proposed genetic algorithm is effective.