THE ECONOMIC LOT AND DELIVERY SCHEDULING PROBLEM - POWERS OF 2 POLICIES

Authors
Citation
J. Hahm et Ca. Yano, THE ECONOMIC LOT AND DELIVERY SCHEDULING PROBLEM - POWERS OF 2 POLICIES, Transportation science, 29(3), 1995, pp. 222-241
Citations number
53
Categorie Soggetti
Transportation,Transportation
Journal title
ISSN journal
00411655
Volume
29
Issue
3
Year of publication
1995
Pages
222 - 241
Database
ISI
SICI code
0041-1655(1995)29:3<222:TELADS>2.0.ZU;2-Q
Abstract
We investigate the problem of simultaneously scheduling the final prod uction line of a captive supplier and the delivery of components produ ced on that line to an assembly facility that uses these components at a constant rate. The supplier incurs a sequence-independent setup cos t and/or setup time each time the production Line is changed over from one component to another. On the other hand setup costs and times for the assembly facility are negligible. We consider two types of delive ry costs: a fixed charge for each delivery, and a fixed-charge-pertruc k cost. We develop a heuristic procedure to find a cyclic production a nd delivery schedule with the power-of-two property. That is, in each cycle, each component is produced 2(mu) times for some small integer m u, where the value of mu may differ across components. In addition sev eral equally-spaced deliveries occur in each cycle, where the number o f deliveries is equal to the least common multiple of the component pr oduction frequencies. The objective is to find the schedule that minim izes the average cost per unit time of transportation, inventory at bo th the supplier and the assembly facility, and setup costs at the supp lier. Computational results suggest that the heuristic performs well i n an, absolute sense, and that significant savings can be achieved by using coordinated production and delivery schedules rather than approa ches in which they are decided sequentially. The results also indicate that in many situations, pure just-in-time policies (in which product ion and delivery frequencies are equal) are far from optimal. Our mode l provides a basis for determining the type and extent of improvements needed in the quest for just-in-time.