eResearch@Ozyegin


eResearch@Ozyegin is an academic, open-access repository. It aims to collect, preserve and make Ozyegin University’s scientific output available online, without any or the least financial, legal or technical restrictions, in order to increase the impact and the visibility of the institution and its authors. It was established in 2010 to support the dissemination of knowledge produced by the University members to the wider community both locally and globally.


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OtherPublicationOpen Access
ILO Hanehalkı Araştırması Anketi - 2024
Sümer, H. Canan; Psychology; SÜMER, Hayriye Canan
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ArticlePublicationOpen Access
Inquiring the generative capacity of urban abstraction and mapping for first-semester basic design studio
(Nilay Özsavaş Uluçay, 2023-06-01) Yorgancıoğlu, Derya; Güngör, Beyza Şat; Aman, Doğa Dinemis; Faculty of Architecture and Design; Interior Architecture and Environmental Design; YORGANCIOĞLU, Derya; ŞAT, Beyza; AMAN, Doğa Dinemis
The development of students’ critical and creative thinking skills is at the core of the first-semester basic design studio. Students’ perceptual experiences of their environment form the key references of abstraction in this beginning phase. This paper inquires studio approach based on abstraction and mapping as tools for intertwining visual reasoning and bodily experiences in the design process. Focusing on the case study of a basic design studio assignment, the authors analyze the structure, application, and products of the “Urban Abstraction and Mapping” project. The study adopted the case-study method as part of qualitative research approach and dwelled on researchers’ first-hand interaction with a phenomenon within its real-life context, ARCH/MIM101 studios. The findings showed that abstraction and mapping strategies based on students’ bodily experiences in urban contexts raised awareness of design as a generative and iterative research process. Students who were able to reveal and reconstruct the relationship between different forms of knowledge through experiential and conceptual levels of the design process managed to develop heuristic 2D and 3D design strategies. The findings of this study provide a ground for discussions on the effectiveness of teaching/learning methods applied in the introductory level of design education.
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Master ThesisPublication
Matheuristic for multi-period home healthcare routing and scheduling problem : a real life case study
(2023) Selçuk, Yağmur Selenay; Göktürk, Elvin Çoban; Koyuncu, Burcu Balçık; Göktürk, Elvin Çoban; Yıldırım, U. M.; Department of Industrial Engineering; Selçuk, Yağmur Selenay
The aging population's exponential growth has exerted considerable pressure on healthcare systems, necessitating the provision of enhanced healthcare services tailored to meet the unique needs of older adults, individuals with disabilities, and chronic patients. As a result, healthcare providers aim to offer varying healthcare services to patients in their homes, with the objective of improving the quality of care and optimizing the management of health systems. This thesis studies a home healthcare routing and scheduling problem (HHCRSP) over a multi-period planning horizon, considering caregivers' lunch breaks, prior service type, and patients' preferences. In this HHCRSP, some patients needing blood draw, and they have to be visited before noon, guaranteeing the corresponding caregiver's return to the hospital's lab before noon. Additionally, patients have preferred time windows for each day, corresponding to times due to reasons such as the need for someone to support them with the patients. In the thesis, the objective function is minimizing the total routing costs of caregivers' vehicles and the penalty costs incurred when patients cannot receive services within their preferred time windows. Our study is motivated by a real-life hospital that provides home healthcare service (HHCS). We develop a mixed-integer linear programming (MILP) model and propose a simulated annealingbased matheuristic algorithm (SAMA) that decomposes the original problem into two phases. Furthermore, we conduct a comparative analysis of the k-nearest-neighbour (KNN) algorithm, utilizing various k values to predict service times. The results of our study demonstrate significant improvements, up to 98.64% in cost-effectiveness achieved by the MILP in small-sized instances, and 98.58% by the SAMA in medium and large-sized instances, compared to the existing system in the motivational hospital. The numerical analysis provides insights for healthcare providers and policymakers in their efforts to optimize HHCS.