Show simple item record

dc.contributor.advisorGökbayrak, Kağan
dc.contributor.authorGüleçyüz, Süheyl
dc.date.accessioned2018-02-27T06:10:21Z
dc.date.available2018-02-27T06:10:21Z
dc.date.copyright2018-01
dc.date.issued2018-02
dc.date.submitted2018-02-26
dc.identifier.urihttp://hdl.handle.net/11693/35988
dc.descriptionCataloged from PDF version of article.en_US
dc.descriptionThesis (M.S.): Bilkent University, Department of Industrial Engineering, İhsan Doğramacı Bilkent University, 2018.en_US
dc.descriptionIncludes bibliographical references (leaves 78-83).en_US
dc.description.abstractThe state of the economy may fluctuate due to several factors, and the customer demand is a affected from the fluctuations of the state of the economy. Although the inventory holders can predict the state of the economy based on the demand realizations, they generally do not have the true state information. The lack of information can be extended to the transition probabilities in the state, and the demand distributions associated with each state. Further extensions may include the actual number of demand states. We consider a single-item, periodic-review inventory system with Markov-modulated discrete-valued demand, constant lead time, and full backlogging. The true demand distribution state is partially observed based on the realized demands. We study the infinite horizon average cost minimization problem, in which the optimal inventory replenishment policy is a state-dependent base-stock policy. We develop a local search method based on finite perturbation analysis (FPA) to find the base-stock levels for a finite number of discretized state beliefs. We then extend our search method to the unknown transition matrix and demand distribution case. We compare the FPA-based local search algorithm with a myopic base-stock policy, the Viterbi algorithm, and the sufficient statistics method, in terms of the average cost. Finally, we analyze how the average cost changes with respect to the estimated number of demand states when the actual number of states is unknown.en_US
dc.description.statementofresponsibilityby Süheyl Güleçyüz.en_US
dc.format.extentxvi, 98 pages : charts (some color) ; 30 cmen_US
dc.language.isoEnglishen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectInventory Systemsen_US
dc.subjectHidden Markov Modelsen_US
dc.subjectBase-Stock Policyen_US
dc.subjectFinite Perturbation Analysisen_US
dc.subjectSimulationen_US
dc.subjectBaum-Welch Algorithmen_US
dc.titleFinite perturbation analysis methods for optimization of inventory systems with non-stationary Markov-modulated demand and partial informationen_US
dc.title.alternativeTalep dağılımının saklı Markov modellerine bağlı olarak değiştiği envanter sistemleri için sonlu sarsınım analizi yöntemlerien_US
dc.typeThesisen_US
dc.departmentDepartment of Industrial Engineeringen_US
dc.publisherBilkent Universityen_US
dc.description.degreeM.S.en_US
dc.identifier.itemidB157537


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record