具有学习退化效应的TFT-LCD面板成盒多目标调度问题研究

针对薄膜晶体管液晶显示器(TFT-LCD)面板成盒生产规模性、多产品混线生产、机台特性复杂的特点,引入学习效应和退化效应,以最小化最大完成时间、机器等待时间、工件加权延期时间为目标函数,构建具有学习退化效应的TFT-LCD面板成盒多目标调度模型。基于两段式及IMM编码,采用多目标布谷鸟算法,结合双元锦标赛及动态淘汰规则,依据聚集距离密度评价指标构建帕累托非劣解集,对TFT-LCD面板成盒多目标调度问题进行求解。仿真结果表明,布谷鸟算法寻优能力优于精英保留贪婪解码遗传算法与工序期望最短完成时间调度规则等。通过实验,分析不同学习率和退化因子对调度结果的影响。

TFT-LCD Cell Assembly Multi-objective Scheduling Problem with Learning and Deterioration Effects

In view of characteristics of the scale, multi product and multi machine features of a TFT-LCD cell assembly stage, the learning and deterioration effects were introduced. The minimization of the maximum completion time, the total wait time and the weighted delay time of the machine were taken as objective functions, and a multi-objective TFT-LCD cell scheduling model was built. Based on the two segments and IMM encoding, the multi-objective cuckoo algorithm combined with the Pareto set with dual championship, the dynamic elimination rules and the cluster distance density evaluation index to solve the multi-objective TFT-LCD cell scheduling problem. The simulation results show that the cuckoo algorithm is superior to the elitist reservation greedy decoding genetic algorithm, the process expectation shortest completion time scheduling regulation, etc. Through experiments, the effects of different learning rates and deterioration factors on scheduling results were analyzed.