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个性化产品的生产过程具有非重复性,致使工序的加工时间不确定且难以估计其概率信息。因此,传统的确定调度和随机调度方法不再适用。采用最小化最大后悔值的鲁棒优化方法,研究变速平行机加工环境下个性化产品的生产调度问题。首先,采用区间情景描述不确定的加工时间,构建基于后悔值准则的个性化产品鲁棒调度模型;其次,证明任意调度方案带来的最大后悔值可通过求解一个指派问题得到;然后,提出基于混合整数规划和迭代松弛过程的两种精确算法获取最优解;最后,通过仿真实验评估两种精确算法的有效性,结果表明基于混合整数规划的精确算法明显优于迭代松弛算法,并且可以快速求解中小规模的调度问题。
Non-repetitive production process of personalized products, resulting in the process of processing time is uncertain and difficult to estimate the probability of information. Therefore, the traditional deterministic scheduling and stochastic scheduling methods are no longer applicable. The minimization of maximum regret values is used to study the production scheduling problem of personalized products under variable speed parallel machining environment. Firstly, the interval scenario is used to describe the uncertain processing time and a personalized product robust scheduling model based on the regret value criterion is constructed. Secondly, the maximum regret value of any scheduling solution is proved by solving an assignment problem. Then, Mixed integer programming and iterative relaxation process. Finally, the effectiveness of the two exact algorithms is evaluated through simulation experiments. The results show that the precision algorithm based on mixed integer programming is obviously better than the iterative relaxation algorithm, and can be fast Solve the small-scale scheduling problem.