Some Approximations in Multi-Item, Multi-Echelon Inventory Systems for Recoverable Items,
Abstract
The optimization problem as formulated in the METRIC model takes the form of minimizing the expected number of total system backorders in any two-echelon inventory system subject to a budget constraint. To solve this problem, one needs to find the optimal Lagrangian multiplier a Lagrangian multiplier is a reduction in backorder or shortage that can come about because of an increase in the investment in inventory) associated with the given budget constraint. For any large scale inventory system, this task is computationally not trivial. Fox and Landi proposed one method which was a significant improvement over the original METRIC algorithm. A method for estimating the value of the optimal Lagrangian multiplier used in the Fox-Landi algorithm is developed, alternative ways for determining stock levels are presented, and these proposed approaches with the Fox-Landi algorithm are compared using two hypothetical inventory systems--one involving 3 bases and 75 items; the other has 5 bases and 125 items. The comparison shows that the computational time can be reduced by nearly 50 percent. Another factor that contributes to the higher requirement for computational time in obtaining the solution to two-echelon inventory systems is that it has to optimally allocate stock to the depot as well as to bases for a given total system stock level.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 01, 1976
- Accession Number
- ADA040865
Entities
People
- John A. Muckstadt
Organizations
- RAND Corporation