TIME‐BASED PRICING AND LEADTIME POLICIES FOR A BUILD‐TO‐ORDER MANUFACTURER

We studied time‐based policies on pricing and leadtime for a build‐to‐order and direct sales manufacturer. It is assumed that the utility of the product varies among potential customers and decreases over time, and that a potential customer will place an order if his or her utility is higher than the manufacturer's posted price. Once an order is placed, it will be delivered to the customer after a length of time called “leadtime.” Because of the decrease in a customer's utility during leadtime, a customer will cancel the order if the utility falls below the ordering price before the order is received. The manufacturer may choose to offer discounted prices to customers who would otherwise cancel their orders. We discuss two price policies: common discounted price and customized discounted price. In the common discounted price policy, the manufacturer offers a single lower price to the customers; in the customized discounted price policy, the manufacturer offers the customers separately for individual new prices. Our analytical and numerical studies show that the discounted price policies results in higher revenue and that the customized discounted price policy significantly outperforms the common discounted price policy when product utility decreases rapidly. We also study two leadtime policies when production cost decreases over time. The first uses a fixed leadtime, and the second allows the leadtime to vary dynamically over time. We find that the dynamic leadtime policy significantly outperforms the fixed leadtime policy when the product cost decreases rapidly.     

A SIMPLE HEURISTIC FOR DYNAMIC ORDER SIZING AND SUPPLIER SELECTION WITH TIME‐VARYING DATA

In this paper we consider the problem of supplier selection and purchase order sizing for a single item under dynamic demand conditions. Suppliers offer all‐units and/or incremental quantity discounts, which may vary over time. Although the problem refers to a typical planning task of a purchasing agent, which is often solved without algorithmic assistance, in an eBusiness (b2b) environment, the need for the integration of an automatic performance of this planning task into a web‐based procurement process becomes evident. A new model formulation for this problem is developed, and a simple but easily extendible heuristic procedure is presented and tested. The heuristic is implemented as part of the Advanced Planner and Optimizer (apo) software of SAP AG, Walldorf, Germany.     

LOT‐SIZING RULE AND FREEZING THE MASTER PRODUCTION SCHEDULE UNDER CAPACITY CONSTRAINT AND DETERMINISTIC DEMAND

This paper investigates the performance impact of lot‐sizing rule (LSR) selection and freezing of the master production schedule (MPS) in multi‐item single‐level systems with a single resource constraint under deterministic demand. The results of the study show that the selection of LSRS and the parameters for freezing the MPS have a significant impact on total cost, schedule instability, and the service level of the system. However, the selection of LSRS does not significantly influence the selection of the MPS freezing parameters. The basic conclusions concerning the performance of the freezing parameters under a capacity constraint agreed with previous research findings without consideration of capacity constraints.     

MANAGING A FLOW LINE WITH SINGLE‐KANBAN,DUAL‐KANBAN OR CONWIP

To control the production of different parts on a single flow line, managers can choose between the Single‐kanban, Dual‐kanban, and Conwip. This paper therefore compares the three different systems. The results show that Conwip consistently produces the shortest mean customer wait time and lowest total work‐in‐process. Our results also contradict the finding of a previous study, which showed that Dual‐kanban performed better than Single‐kanban. The different findings can, however, be attributed to the use of a material transfer policy, which favors the Dual‐kanban modeled in the previous study. Our study shows that transferring replenished containers immediately to downstream stations, increasing the number of cards, and reducing the withdrawal cycle reduce the mean customer wait time significantly.     

OPTIMAL AND HEURISTIC SOLUTIONS FOR THE MULTI‐ITEM NEWSVENDOR PROBLEM WITH A SINGLE CAPACITY CONSTRAINT

This research considers a multi‐item newsvendor problem with a single capacity constraint. While this problem has been addressed in the literature, the focus here is on developing simple, closed‐form expressions for the order quantities. The benefit of such an approach is that the solutions are straightforward to calculate and have managerial appeal. Additionally, we show these expressions to be optimal under a variety of conditions. For more general cases when these optimality conditions do not hold, we use these expressions as heuristic solutions. Via computational studies, we demonstrate that these heuristics are extremely effective when the optimality conditions are not satisfied.