Determination of Sustainable Waste Management Strategies in Smart Cities Using Fuzzy Multi-Criteria Decision Approach
Tezin Türü: Yüksek Lisans
Tezin Yürütüldüğü Kurum: Yıldız Teknik Üniversitesi, Fen Bilimleri Enstitüsü, Çevre Mühendisliği, Türkiye
Tezin Onay Tarihi: 2023
Tezin Dili: İngilizce
Öğrenci: BİHTER GİZEM DEMİRCAN
Danışman: Kaan Yetilmezsoy
Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
Özet:
The integration of smart city technologies into waste management is a challenging field for decision-makers due to its multi-variate, multi-limiting and multi-stakeholder structure, despite its contribution to the ecological and economic understanding of cities' sustainability. The success of smart sustainable waste management strategies depends on many environmental, technical, economic and social variables, and many stakeholders are involved in the processes. Using Fuzzy Multi-Criteria Decision-Making methods helps decision makers determine effective, affordable, and acceptable smart waste management strategies. Although MCDM methods are widely used in various environmental engineering applications, the determination of smart sustainable waste management strategies using these methods has not yet received enough attention in the literature. This study aims to contribute to this gap in the literature by evaluating four different smart waste management strategies using a hybrid fuzzy MCDM method. The performance of the proposed strategy alternatives according to fifteen sub-criteria under four main criteria selected from the literature was evaluated by a combined application of Fuzzy Analytic Hierarchy Process (Fuzzy AHP) and Fuzzy Technique for Order Preference by Similarity to Ideal Solution (Fuzzy TOPSIS). For this evaluation, the subjective opinions of ten different experts working in academia, in the private sector or in the public sector were obtained using the prepared questionnaires. To test the reliability and stability of the obtained performance ranking results, a sensitivity analysis was performed using eighteen different scenarios in which the weights of the sub-criteria were increased, decreased or changed at different rates. As a result of the analysis, it turned out that the initially obtained ranking is robust to the sub-criteria weight changes, since the performance ranking of the alternatives did not change.