Kuşakcı, Ali Osman
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Araştırma projeleri
Organizasyon Birimleri
Yönetim Bilimleri Fakültesi, İşletme Bölümü
Küresel rekabete ayak uydurmak ve sürdürülebilir olmak isteyen tüm şirketler ve kurumlar, değişimi doğru bir şekilde yönetmek, teknolojinin gerekli kıldığı zihinsel ve operasyonel dönüşümü kurumlarına hızlı bir şekilde adapte etmek zorundadırlar.
Adı Soyadı
Ali Osman Kuşakcı
İlgi Alanları
Business Analytics, Artificial Intelligence, Genetic Algorithm, Constrained Optimization
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2 sonuçlar
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Yayın A fuzzy integer programming model to locate temporary medical facilities as part of pre-disaster management(IGI Global, 2019) Kuşakcı, Ali Osman; Kuşakcı, Ali Osman; Kuşakcı, Ali Osman; Ayvaz, Berk; Yönetim Bilimleri Fakültesi, İşletme Bölümü; Yönetim Bilimleri Fakültesi, İşletme BölümüThe number and the scale of natural disasters have drastically increased over the last decades. One of the most vital stages of disaster preparedness is disaster response planning, and it plays an important role in limiting material and immaterial consequences, such as those caused by large scale earthquakes. In order to minimize human suffering and death, the aim of establishing a well-designed humanitarian relief chain must be to provide medicine, water, shelter, emergency food and supplies to the affected areas. From a holistic perspective, providing timely first aid and rapid transfer of injured victims to a medical facility is one of the most essential component of such chain. Thus, the location of first aid hospitals must be determined following a careful thought and planning process. This study presents a fuzzy integer programming model to determine the best location of the temporary hospitals which are expected to support extant state hospitals after a major earthquake. This study applies the proposed fuzzy model to the Üsküdar province of Istanbul and identifies optimum number and locations of field hospitals for a severe earthquake scenario.Yayın Optimization of reverse logistics network of End of Life Vehicles under fuzzy supply: A case study for Istanbul Metropolitan Area(Elsevier, 2019) Kuşakcı, Ali Osman; Kuşakcı, Ali Osman; Kuşakcı, Ali Osman; Ayvaz, Berk; Cin, Emine; Aydın, Nezir; Yönetim Bilimleri Fakültesi, İşletme Bölümü; Yönetim Bilimleri Fakültesi, İşletme BölümüRecycling aims at preventing rapid depletion of natural resources while transforming produced waste into value for economy. However, this process becomes a major challenge in automotive industry, which requires cooperative engagement of multiple players within a complex supply chain. In line with the essence of the topic, government agencies around the world issue directives drawing regulatory frameworks for designing recycling operations comprising various activities such as collection of end-of-life vehicles (ELVs), recovery of reusable components, shredding ELV's body, recycling valuable materials and disposal of the hazardous waste. In general, the amount of returned product in a reverse logistics network is highly uncertain, and the ELV market in Turkey is no exception to this. For that purpose, this study aims developing a fuzzy mixed integer location-allocation model for reverse logistic network of ELVs conforming to the existing directives in Turkey. Accordingly, this study uses a novel approach and assumes that ELV supply in the network is uncertain. The merit of the proposed mathematical model is proved on a real world scenario addressing the reverse logistics design problem for ELVs generated in metropolitan area of Istanbul. The network generated specifies that recycling process is not profitable under the existing circumstances with the given level of supplied ELV and the returned product records per capita in Istanbul are far beyond the EU averages. Consequently, sensitivity analyses question the reliability of the obtained results.