Dominance Conditions for Optimal Order-Lot Matching in the Make-To-Order Production System

Abstract

Order-lot matching is the process of assigning items in lots being processed in the make-to-order production system to meet the due dates of the orders. In this study, an order-lot matching problem (OLMP) is considered to minimize the total tardiness of orders with different due dates. In the OLMP considered in this study, we need to not only determine the allocation of items to lots in the production facility but also generate a lot release plan for the given time horizon. We show that the OLMP can be considered as a special type of machine scheduling problem with many similarities to the single machine total tardiness scheduling problem ( 1 | | ∑ T i ). We suggest dominance conditions for the OLMP by modifying those for 1 | | ∑ T i and a dynamic programming (DP) model based on the dominance conditions. With two example problems, we show that the DP model can solve small-sized OLMPs optimally.

Online and Offline Model for Housekeeping Order Assignment Based on Dynamic Programming Algorithm

“…In 2020, Baek et al [12] proposed a nonlinear integer programming model and developed two different algorithms to improve the usability of the model in real business with large amounts of data. Kim et al [13] considered an order batch matching problem (OLMP) to minimize the total delay of orders with different expiration dates, which is necessary not only to determine the batch allocation in the production facility, but also to generate a batch release plan within a given time period. Based on the DP model with dominant conditions, the advantage condition of OLMP has been proposed.…”