Just-in-Time Smoothing Through Batching
针对混合型号即时生产系统中因型号间准备时间和加工时间差异大导致的生产平滑问题，提出两种方法：一种用多项式时间算法找出所有帕累托最优解，另一种基于韦伯斯特分配法生成周期性均匀生产序列，实验验证了效果。
This paper presents two methods to solve the production smoothing problem in mixed-model just-in-time (JIT) systems with large setup and processing time variability between different models the systems produce. The problem is motivated by production planning at a leading U.S. automotive pressure hose manufacturer. One method finds all Pareto-optimal solutions that minimize total production rate variation of models and work in process (WIP), and maximize system utilization and responsiveness. These Pareto-optimal solutions are found efficiently in polynomial time with respect to total demand by an algorithm proposed in the paper. The other method relies on Daniel Webster's method of apportionment for production smoothing, which produces periodic, uniform, and reflective production sequences that can improve operations management of the JIT systems. Finally, the paper presents the results of a computational experiment with the two methods.