Due Date Assignment for Production Systems
研究动态作业车间中恒定交货期分配策略，通过最小化包含提前、拖期和等待成本的期望总成本，提出一种利用作业在车间总时间分布的算法，可手动计算最优交货期。
This paper is concerned with the study of the constant due-date assignment policy in a dynamic job shop. Assuming that production times are randomly distributed, each job has a penalty cost that is some non-linear function of its due-date and its actual completion time. The due date is found by adding a constant to the time the job arrives to the shop. This constant time allowed in the shop is the lead time that a customer might expect between time of placing the order and time of delivery. The objective is to minimize the expected aggregate cost per job subject to restrictive assumptions on the priority discipline and the penalty functions. This aggregate cost includes (1) a cost that increases with increasing lead times, (2) a cost for jobs that are delivered after the due dates: the cost is proportional to tardiness and (3) a cost proportional to earliness for jobs that are completed prior to the due dates. We present an algorithm for solving this problem and show that the optimal lead time is a unique minimum point of strictly convex functions. The algorithm utilizes analytical procedures; computations can be made manually. No specific distributions are assumed; the distribution of total time a job is in the shop is utilized by the algorithm. This distribution can be theoretical or empirical. An example of a production system is presented.