基于TSP模型求解制丝生产调度问题

Solving production scheduling problem in tobacco primary processing based on TSP model

为进一步优化制丝生产流程,将制丝生产调度问题与TSP(Traveling Salesman Problem)问题进行了映射,基于不考虑时间约束、考虑时间约束、多生产线3种条件分别建立了优化模型,并采用改进的遗传算法进行求解。将宁波卷烟厂4个牌号16批次的制丝生产数据导入所建立的模型进行求解,并将计算结果与实际生产数据进行对比,结果表明:采用优化方法可以得到多种批次生产安排,且均符合时间窗口要求,与实际生产相比卷烟牌号切换次数明显减少,优化效果显著,运算效率可以满足生产要求。该方法可为提高制丝生产精益管理水平提供支持。

In order to further optimize the production flow, the production scheduling problem in tobacco primary processing was mapped with TSP （Traveling Salesman Problem）. Optimization models were established separately on the basis of 3 conditions （without time constraint, with time constraint and multi-line production）, and the models were solved with the modified genetic algorithm. The production data of 16 batches of 4 brands in Ningbo Cigarette factory were introduced into the established models, and the calculated results were compared with the actual production data. The results showed that a number of batch production scheduling plans could be obtained via optimization methods, and all the obtained plans were in compliance with the time window requirements. Comparing with the actual production data, the number of brand switching decreased obviously. The optimization effects of the methods are remarkable and their calculation efficiency meets production requirements. This method provides a support for promoting the lean management level in tobacco primary processing.