Yazar "Ghasemi, Peiman" seçeneğine göre listele

Listeleniyor 1 - 2 / 2
  • Küçük Resim
    Öğe
    Addressing barriers to big data implementation in sustainable smart cities: Improved zero-sum grey game and grey best-worst method
    (Elsevier B.V., 2024) Razavian, Behnam; Hamed, S.Masoud; Fayyaz, Maryam; Ghasemi, Peiman; Özkul, Seçkin; Tirkolaee, Erfan Babaee
    The optimization of sustainable smart cities is an essential endeavor in modern urban development, aiming to enhance the quality of life for citizens while minimizing environmental impacts. Big data plays a critical role in achieving these goals by enabling the collection, analysis, and utilization of vast amounts of information to make informed decisions. However, implementing big data in smart cities faces significant barriers, including data-sharing challenges, technical limitations, and organizational non-cooperation. Addressing these barriers is crucial for the successful deployment of smart city initiatives. We propose a novel approach to tackle these challenges using the Improved Zero-Sum Grey Game (IZSGG) theory and the Grey Best-Worst Method (G-BWM). This method comprehensively analyzes the risks and uncertainties associated with big data implementation in smart cities. By modeling the interactions between different stakeholders and their competing interests, IZSGG theory provides a framework to identify optimal strategies for data management. The G-BWM further refines these strategies by evaluating and prioritizing the various factors influencing big data utilization. Our findings reveal that the worst-case scenario for a smart city involves the simultaneous occurrence of several risks, all of which have positive values, indicating their potential to significantly disrupt smart city operations. The specific risks identified include: the sharing of data and information, the collection and recording of data, technical limitations and challenges associated with technology, the non-cooperation of organizations, and issues related to the interpretation of complex information. The technical barrier is the most significant with a weight of w(T)=0.6152, indicating its critical role compared to other barriers. Within this category, the sub-barrier of technical and technological constraints is particularly critical, with a weight of 0.39267375. © 2024 The Authors
  • Küçük Resim Yok
    Öğe
    A DEA-based simulation-optimisation approach to design a resilience plasma supply chain network: a case study of the COVID-19 outbreak
    (Taylor & Francis Ltd, 2023) Ghasemi, Peiman; Goodarzian, Fariba; Simic, Vladimir; Tirkolaee, Erfan Babaee
    This study develops a novel multi-objective mathematical model for a Plasma Supply Chain Network (PSCN) in order to maximise the coverage of blood donors during periods and minimise the blood transportation costs between different nodes, relocation cost of temporary mobile facilities, inventory holding cost of the blood, and the costs of newly established blood centres. Therefore, the major contribution of this work is the simultaneous consideration of resiliency and efficiency in the proposed PCN during the COVID-19 outbreak. To address the uncertain parameters, Stochastic Chance-Constrained Programming (SCCP) method is applied to the model. Additionally, to solve the PSCN model, the & epsilon;-constraint method is employed for small- and medium-sized problems and then a multi-objective invasive weed optimisation (MOIWO) algorithm is implemented for large-sized problems. To validate the suggested methodology, a variety of problem instances is designed and solved using the solution techniques, considering two assessment metrics of Hyper Volume (HV) and Min Ideal Distance (MID). Moreover, a real case study and sensitivity analyses on significant parameters are conducted to configure the optimal network. Eventually, the obtained results are examined and useful decision aids are suggested.