dc.contributor.advisor | Gökbayrak, Kağan | |
dc.contributor.author | Avcı, Harun | |
dc.date.accessioned | 2018-05-18T11:27:46Z | |
dc.date.available | 2018-05-18T11:27:46Z | |
dc.date.copyright | 2018-05 | |
dc.date.issued | 2018-05 | |
dc.date.submitted | 2018-05-17 | |
dc.identifier.uri | http://hdl.handle.net/11693/46944 | |
dc.description | Cataloged from PDF version of article. | en_US |
dc.description | Thesis (M.S.): Bilkent University, Department of Industrial Engineering, İhsan Doğramacı Bilkent University, 2018. | en_US |
dc.description | Includes bibliographical references (leaves 44-48). | en_US |
dc.description.abstract | We consider a discrete-time in nite-horizon inventory system with full backlogging,
deterministic replenishment lead time, and Markov-modulated demand.
The actual state of demand can only be imperfectly estimated based on past
demand data. We model the inventory replenishment problem as a Markov decision
process with an uncountable state space consisting of both the inventory
position and the most recent belief about the actual state of demand. When the
demand state evolves according to an ergodic Markov chain, using the vanishing
discount method along with a coupling argument, we prove the existence of an
optimal average cost that is independent of the initial system state. With this
result, we establish the average-cost optimality of a belief-dependent base-stock
policy. We then discretize the belief space into a regular grid. The average cost
under our discretization converges to the optimal average cost as the number of
grid points grows large. Finally, we conduct numerical experiments to evaluate
the use of a myopic belief-dependent base-stock policy as a heuristic. On a test
bed of 108 instances, the average cost under the myopic policy deviates by no
more than a few percent from the best lower bound on the optimal average cost
obtained from our discretization. | en_US |
dc.description.statementofresponsibility | by Harun Avcı. | en_US |
dc.format.extent | viii, 48 leaves : charts ; 30 cm | en_US |
dc.language.iso | English | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.subject | Inventory Control | en_US |
dc.subject | Markov-Modulated Demand | en_US |
dc.subject | Partial Observations | en_US |
dc.subject | Long-Run Average Cost | en_US |
dc.subject | Base-Stock Policy | en_US |
dc.title | Structural results for average-cost inventory models with partially observed Markov-modulated demand | en_US |
dc.title.alternative | Saklı Markov süreciyle değişen talep dağılımlı ortalama maliyet envanter modellerinde yapısal sonuçlar | en_US |
dc.type | Thesis | en_US |
dc.department | Department of Industrial Engineering | en_US |
dc.publisher | Bilkent University | en_US |
dc.description.degree | M.S. | en_US |
dc.identifier.itemid | B158355 | |
dc.embargo.release | 2019-01-01 | |