Endüstri Mühendisliği Bölümü

Permanent URI for this communityhttps://hdl.handle.net/20.500.12416/16

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Citation - WoS: 16
Citation - Scopus: 18
Determination of Equivalent Warehouses in Humanitarian Logistics by Reallocation of Multiple Item Type Inventories
(Elsevier, 2021) Ertem, Mustafa Alp; Demirbas, Sefika
Prepositioning freight containers for storage of relief supplies can be considered an alternative to warehousing with shelves. Recently, 25 container warehouses are located in different cities in Turkey to deliver relief supplies to beneficiaries quickly. We take this existing situation as given and investigate if this investment could be utilised better. The available inventory (i.e., tents, beds, blankets) in these container warehouses is currently not used efficiently. Some warehouses store one type of item and none from other types. Therefore, several warehouses must be activated during a response operation to fully satisfy the beneficiaries' needs for each relief item type. We aim to investigate the benefits of operating equivalent (i.e., a proper inventory level from each relief item type) warehouses while reallocating a total available inventory for better coordination. A locationreallocation type of mathematical model is tested with real-life data from past earthquakes. Three to eight container warehouses are recommended to be converted to an equivalent type. The results indicate potential savings for the proposed model, and this potential is more visible in large-scale demand instances than in small ones.
Citation - WoS: 8
Citation - Scopus: 12
Estimating Parameters of a Multiple Autoregressive Model by the Modified Maximum Likelihood Method
(Elsevier, 2010) Bayrak, Oezlem Tuerker; Akkaya, Aysen D.
We consider a multiple autoregressive model with non-normal error distributions, the latter being more prevalent in practice than the usually assumed normal distribution. Since the maximum likelihood equations have convergence problems (Puthenpura and Sinha, 1986) [11], we work Out modified maximum likelihood equations by expressing the maximum likelihood equations in terms of ordered residuals and linearizing intractable nonlinear functions (Tiku and Suresh, 1992) [8]. The solutions, called modified maximum estimators, are explicit functions of sample observations and therefore easy to compute. They are under some very general regularity conditions asymptotically unbiased and efficient (Vaughan and Tiku, 2000) [4]. We show that for small sample sizes, they have negligible bias and are considerably more efficient than the traditional least Squares estimators. We show that Our estimators are robust to plausible deviations from an assumed distribution and are therefore enormously advantageous as compared to the least squares estimation. We give a real life example. (C) 2009 Elsevier B.V. All rights reserved.
Citation - WoS: 14
Citation - Scopus: 21
Intermodal Transportation in Humanitarian Logistics With an Application To a Turkish Network Using Retrospective Analysis
(Elsevier, 2022) Akdogan, Muharrem Altan; Kahya, Melike; Ertem, Mustafa Alp
In the event of disruptions in a transportation network following a disaster, humanitarian organizations find it challenging to provide basic requirements for beneficiaries. Demand may be met using intermodal transportation as an alternative when the unimodal transportation infrastructure is damaged. This study proposes a mathematical model for utilizing intermodal transportation using 40 ft standard containers while delivering relief supplies by road, rail, and sea modes. The proposed model is a capacitated multi-period multicommodity intermodal network flow model in which relief supplies are delivered to beneficiaries in three echelons (i.e., supply, intermodal hub, and demand). The Turkish Disaster and Emergency Management Presidency's container warehouses (i.e., supply), logistics centers and container ports (i.e., intermodal hubs) are utilized to test the mathematical model with real-life demand parameters. Retrospective analysis was performed to determine the most frequently used container warehouses, logistics centers, and origin-destination pairs. Hence, an increase in operational capacity and infrastructure reinforcement is recommended to mitigate the effects of future disasters. We found that intermodal transportation is more robust to network disruptions in rapidly delivering relief supplies. We observed that intermodal transportation is utilized in disasters with more than 50,000 beneficiaries or disrupted unimodal infrastructure. For instance, after the future Istanbul earthquake, it would be impossible to deliver the relief materials only by road transportation within the urgent response period. Thus, the benefits of intermodal transportation in humanitarian logistics are more visible in large-scale disasters in which transportation resources are scarce, and transportation infrastructure is more likely to be destroyed.

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