Kuşakcı, Ali Osman

Profil fotoğrafı
 E-posta Adresi
aliosman.kusakci@ihu.edu.tr
ORCID Profili
0000-0003-1411-0369
WoS Profili
AAG-5110-2019
Scopus Profili
55330793300
YÖK Araştırmacı Profili
43DD5E590083C016
Google Akademik Profili
YZi-UJQAAAAJ&hl=tr&oi=ao
TR-Dizin Profili
720523
Web Sitesi
akademik.ihu.edu.tr/tr/aliosman-kusakci

Araştırma projeleri

Organizasyon Birimleri

Organizasyon Birimi Logosu
Organizasyon Birimi
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

Kurumdaki Durumu

Aktif Personel

Filtreler

20211
Filtreleri Sıfırla

Ayarlar

WoS Q: Q4 ×

Arama Sonuçları

Listeleniyor 1 - 1 / 1
  • Yayın
    Designing reverse logistics network for end-of-life vehicles: A sustainability perspective in a fragile supply chain
    (The International Journal of Industrial Engineering, 2021) Kuşakcı, Ali Osman; Kuşakcı, Ali Osman; Ayvaz, Berk; Kuşakcı, Ali Osman; Aydın, Nezir; Ertaş, Emine; Yönetim Bilimleri Fakültesi, İşletme Bölümü; Yönetim Bilimleri Fakültesi, İşletme Bölümü
    Environmental guidelines in the automotive industry greatly emphasize the recycling, remanufacturing, and recovering of end-of-life vehicles (ELVs). Given the principle of extended producer responsibility, developing an effective reverse logistics network is the most significant digit ahead of the industry. However, initial attempts addressing the reverse logistics network design (RLND) problem were short-sighted, focusing on cost minimization. Undoubtedly, the whole concept of recycling was founded on the pillars of sustainability. Accordingly, reverse logistics network design must be motivated by long-term environmental and societal benefits. This fact has become even more prominent in the current pandemic environment as COVID-19 has added serious uncertainties and risks to the supply chain processes. This paper reiterates the essence of sustainability goals and proposes a multi-objective fuzzy mathematical model to RLND problem for ELVs under such a fragile and fuzzy environment. The coverage of the proposed model is to optimally determine the locations and numbers of the facilities and the flows among them concerning environmental, social, and economic aspects. Hence, the model aims to reach a robust compromise solution that leads to a resilient network design. A real case study on the ELV market in Istanbul/Turkey proves the merit of the developed model.