In this dissertation, we consider a multi-item two-echelon inventory distribution system
in which the central warehouse operates with (Q, R) policy, and each local warehouse
implements base-stock policy. The objective is to find the policy parameters
minimizing the relevant system-wide costs subject to an aggregate mean response
time constraint at each facility.
We first propose an exact solution procedure based on a branch-and-price algorithm
to find the relevant policy parameters of the system considered. Then, we propose
four alternative heuristics to find the optimal or near-optimal policy parameters of
large practical-size systems. The first heuristic, which we call the Lagrangian heuristic,
is based on the simultaneous approach and relies on the integration of a column
generation method and a greedy algorithm. The other three heuristics are based on
the sequential approach, in which first the order quantities are determined using a
batch size heuristic, then the reorder levels at the central warehouse and the basestock
levels at the local warehouses are determined through the same method used for the Lagrangian heuristic. We also propose a lower bound for the system-wide
cost. Later, we extend our study to compound Poisson demand.
The performance of the Lagrangian heuristic is found to be extremely well and improves
even further as the number of parts increases. Also the computational requirement
of the heuristic is quite tolerable. This makes the heuristic very promising for
large practical industry-size problems. The performance of the sequential heuristics
is also satisfactory, but not as much as the Lagrangian heuristic.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12612685/index.pdf |
| Date | 01 October 2010 |
| Creators | Topan, Engin |
| Contributors | Bayindir, Zeynep Pelin |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | Ph.D. Thesis |
| Format | text/pdf |
| Rights | To liberate the content for public access |
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