PRACTICE‐FOCUSED RESEARCH ISSUES FOR SCHEDULING SYSTEMS*

Scheduling research has had relatively little impact on manufacturing practice, yet within the last several years, there has been an explosive growth in the development and implementation of computer‐based scheduling systems in industry. Changes in the environment have increased the stakes and the opportunities for the results of scheduling research to influence manufacturing competitiveness. This paper draws on field‐related experiences with the development and implementation of scheduling systems to propose high‐impact research topics.     

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.     

JOB RELEASE CONTROL USING A CYCLIC SCHEDULE*

In just‐in‐time inventory management in any manufacturing setting, the general idea has been to release jobs as late as possible (to reduce inventory costs) while still having them arrive at bottleneck machines in time to maintain the desired throughput (by not starving a bottleneck machine). When a cyclic schedule is employed, the throughput is determined by a cyclic sequence of operations known as the cyclic critical path. These operations are not, in general, all performed on a single bottleneck machine. We present an algorithm for releasing jobs that treats this cyclic critical path as the bottleneck. Although this algorithm has the somewhat complex task of not delaying any of these operations on the cyclic critical path, it is greatly simplified by being able to take advantage of the fixed sequence of the cyclic schedule. The result is that the algorithm is relatively simple to implement. Although it uses a simulation‐based analysis, this analysis can all be done and the necessary results stored in advance of its use. We test the algorithm in a job shop environment with stochastic operation times. This algorithm is shown to be effective at reducing inventory while avoiding decreases in throughput.     

MULTI‐VENDOR SOURCING IN A RETAIL SUPPLY CHAIN*

This paper describes a methodology for managing capacity, inventory, and shipments for an assortment of retail products produced by multiple vendors. The vendors differ in lead times, costs, and production flexibility. Product demand is uncertain and fluctuates over time. We develop an optimization model to choose the production commitments that maximize the retailers expected gross profit, given demand forecasts and vendors capacity and flexibility constraints. The model has been incorporated into a decision support system, developed in collaboration with supply chain planners at a global retailer of seasonal and fashion merchandise. The software has been tested by two major retailers.