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Topan, Engin

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Profile URL
https://hdl.handle.net/20.500.12416/9166
Name Variants
Topan, E.
Job Title
Yrd. Doç. Dr.
Email Address
etopan@cankaya.edu.tr
Main Affiliation
06.04. Endüstri Mühendisliği
Endüstri Mühendisliği
06. Mühendislik Fakültesi
01. Çankaya Üniversitesi
Status
Former Staff
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ORCID ID
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID

Sustainable Development Goals

SDG data is not available
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Scholarly Output

3

Articles

3

Views / Downloads

13/0

Supervised MSc Theses

0

Supervised PhD Theses

0

WoS Citation Count

38

Scopus Citation Count

55

WoS h-index

3

Scopus h-index

3

Patents

0

Projects

0

WoS Citations per Publication

12.67

Scopus Citations per Publication

18.33

Open Access Source

1

Supervised Theses

0

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JournalCount
Annals of Operations Research1
Journal of the Operational Research Society1
Operations Research Letters1
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2010 - 20123
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Now showing 1 - 3 of 3
  • Thumbnail Image
    Article
    Citation - WoS: 9
    Citation - Scopus: 13
    Multi-Item Two-Echelon Spare Parts Inventory Control Problem With Batch Ordering in the Central Warehouse Under Compound Poisson Demand
    (Palgrave Macmillan Ltd, 2012) Bayindir, Z. P.; Topan, E.
    We consider a multi-item two-echelon spare part inventory system in which the central warehouse operates under an (nQ, R) policy and the local warehouses implement order-up-to S policy, each facing a compound Poisson demand. The objective is to find the policy parameters minimizing expected system-wide inventory holding and fixed ordering costs subject to an aggregate mean response time constraint at each warehouse. In this paper, we propose four alternative approximations for the steady state performance of the system; and extend a heuristic and a lower bound proposed under Poisson demand assumption to the compound Poisson setting. In a computational study, we show that the performances of the approximations, the heuristic, and the lower bound are quite satisfactory; and the relative cost saving of setting an aggregate service level rather than individually for each part is quite high. Journal of the Operational Research Society (2012) 63, 1143-1152. doi: 10.1057/jors.2011.125 Published online 30 November 2011
  • Thumbnail Image
    Article
    Citation - WoS: 6
    Citation - Scopus: 7
    An Approximation for Kanban Controlled Assembly Systems
    (Springer, 2011) Avsar, Zeynep Muge; Topan, Engin
    An approximation is proposed to evaluate the steady-state performance of kanban controlled two-stage assembly systems. The development of the approximation is as follows. The considered continuous-time Markov chain is aggregated keeping the model exact, and this aggregate model is approximated replacing some state-dependent transition rates with constant rates. The approximate aggregate model is, then, decomposed into submodels and a product-form steady-state distribution is obtained for each submodel. Finally, the submodels are combined in such a way that the size of the problem becomes independent of the number of kanbans. This leads to the computational advantage in solving the combined model using numerical matrix-geometric solution algorithms. Numerical comparisons of the combined model with simulation, exact model, approximate aggregate model and an approximation in the literature show that the proposed approximation performs well in terms of accuracy and computational burden.
  • Thumbnail Image
    Article
    Citation - WoS: 23
    Citation - Scopus: 35
    An Exact Solution Procedure for Multi-Item Two-Echelon Spare Parts Inventory Control Problem With Batch Ordering in the Central Warehouse
    (Elsevier Science Bv, 2010) Tan, Tarkan; Bayindir, Z. Pelin; Topan, Engin
    We consider a multi-item two-echelon inventory system in which the central warehouse operates under a (Q, R) policy, and the local warehouses implement basestock policy. An exact solution procedure is proposed to find the inventory control policy parameters that minimize the system-wide inventory holding and fixed ordering cost subject to an aggregate mean response time constraint at each facility. (C) 2010 Elsevier B.V. All rights reserved.