We study extensions of the classical single machine common due-date (CON) and common due-window (CONW) assignment problems to the setting of lot scheduling. In the CON problem, all the jobs share a common due-date, and jobs completed prior to or after the due-date are penalized according to their earliness/tardiness. In CONW, there exists a time interval, such that jobs completed within this interval are not penalized. In both cases the due-date/due-window are decision variables. In lot scheduling, a number of customer orders of different sizes may be processed in the same lot. We allow order splitting between consecutive lots. The objective is to find the order allocation to lots, such that the total cost of earliness, tardiness and due-date/due-window is minimized. Given \(n\) orders, and under the very realistic assumption that the lot capacity is of the order of \(n\), we introduce polynomial time dynamic programming algorithms for both extensions. Our numerical tests indicate that both algorithms can easily solve medium-size problems.

我们研究了经典单机的公共到期日（CON）和公共到期窗口（CONW）分配问题对批次调度设置的扩展。在CON问题中，所有作业共享一个共同的截止日期，并且在截止日期之前或之后完成的作业将根据其早/迟情况受到处罚。在CONW中，存在一个时间间隔，因此在该间隔内完成的作业不会受到惩罚。在这两种情况下，截止日期/到期窗口都是决策变量。在批次计划中，可以在同一批次中处理许多不同大小的客户订单。我们允许在连续的批次之间拆分订单。目的是找到对批次的订单分配，以使尽早，拖延和到期日/到期日的总成本最小化。给定\（n \）阶，并且在非常现实的假设（批处理量为\（n \）的阶数）下，我们针对这两种扩展引入了多项式时间动态规划算法。我们的数值测试表明，两种算法都可以轻松解决中等大小的问题。