Sürdürülebilir Kalkınma Amaçları
Yayınlar
- MakaleAçık Erişim2025Scopus SJRQ1Selection of the central composting facility for organic wastes through the Bayesian best worst method and Geographic information system incorporation: The case of Istanbul
Güler, Mustafa; Samastı, Mesut; Yücesan, Melih; Gül, Muhammet; Çelik, Erkan; Ciner, Miraç Nur; Algorabi, Ömer
The rapid increase in municipal solid waste (MSW) generation, driven by population growth and unplanned urbanization, has made the location of organic waste collection and disposal facilities a critical issue for metropolitan cities. Improper waste management practices threaten environmental sustainability, human health, and urban futures. This study applies multicriteria decision-making (MCDM) methods to identify the optimal placement for a central composting facility in Istanbul. A novel MCDM mechanism was developed, building on existing methods and addressing a gap in the literature. While determining the criteria, academic studies on this subject were researched in depth and the criteria used in these studies were brought together to obtain 28 criteria. The study assessed 28 criteria using the Bayesian Best-Worst Method (BWM) to determine their relative importance. These weights were then integrated into a Geographic Information System (GIS) to produce a suitability map, highlighting the most appropriate locations for the facility. Based on this analysis, the Çatalca Karacabey region was identified as the optimal site, ensuring reduced environmental impact and improved efficiency in organic waste management. The study contributes both theoretically and practically to the field, offering a robust framework for sustainable waste facility siting and providing actionable insights for urban governance. The study provides valuable insights for facility siting and urban governance, while highlighting areas for future research.
AtıfScopus5WoS4
İncele - BildiriYalnız künye2024Scopus SJRQ4Constructing the Criteria in Determining the Product Groups for Agriculture 4.0 Applications
Erdoğan, Melike; Konurhan, Zekeriya; Yücesan, Melih; Gül, Muhammet; Mirzazadeh, A.; Molamohamadi, Z.; Erdebilli, B.; Babaee Tirkolaee, E.; Weber, G.-W.
With Agriculture 4.0, the use of techniques such as sensors, robots, artificial intelligence, and machine learning in agriculture has started. It is aimed to increase productivity in agriculture by reducing food loss and waste through Agriculture 4.0. It is a critical decision to determine which products should be handled first for Turkey to benefit from the advantages of Agriculture 4.0 as soon as possible compared to developed countries in the field of agriculture. At this point, the problem of which factors should be addressed in the determination of product & product groups arises. To handle this, in this study, a multi-criteria analysis has been applied to prioritize the factors that should be considered in the determination of the critical fruit and vegetable group for export, which should be considered as a priority within the scope of Agriculture 4.0. In this context, a multi-criteria analysis has been carried out by adopting the Bayesian Best Worst Method BWM (B-BWM), which is an improved version of a pairwise comparison-based BWM method and applied to group decisions. As a result of the analysis, the most important and least important criteria to be used in determining which products or product groups are more suitable for Agriculture 4.0 applications in Turkey and which should be invested in priority have been determined.
- MakaleAçık Erişim2023Scopus SJRQ3Investigation of issues affecting thermal comfort in water system underfloor heating applications of buildings with Bayesian networks
Erkol, Samet; Yücesan, Melih; Gül, Muhammet; Güneri, Ali Fuat
Thermal comfort is related to the stability of the ambient temperature. Constant changes in ambient temperature appear as a situation that negatively affects comfort. The selected building systems must be arranged to maintain this stability for the continuity of thermal comfort. In this study, issues affecting thermal comfort in water system underfloor heating applications of buildings are handled and analyzed using the Bayesian Network modeling methodology. Visual examples of the problems encountered in field applications are also given. Three different scenarios are tested with the constructed Bayesian Network model. In the first scenario, assumed that mechanical project failures were prevented. In this case, it was observed that the failure rate decreased by about 5%. In the second scenario, assumed that mechanical application failures are prevented along with mechanical project failures. The failure rate decreased by 11% compared to the first situation. The third scenario assumed that the mechanical project preparation phase was concluded without any problems, the mechanical project was implemented without any failures, and the mechanical system was commissioned without any problems. In the last scenario, the failure rate decreased by 14% compared to the first case, and the probability of not providing thermal comfort remained at 2%. As a result of these three scenarios, the possibility of not providing thermal comfort in the underfloor heating system is detailed and interpreted.
- MakaleAçık Erişim2023Scopus SJRQ1A comparative framework for criticality assessment of strategic raw materials in Turkey
Göçmen Polat, Elifcan; Yücesan, Melih; Gül, Muhammet
The rapid development of innovative technologies, population growth, shifting resource management patterns, and decarbonization challenges are expected to increase the demand for raw materials labeled as critical in the following years. The increasing concerns have led to evaluate the critical raw materials (CRMs) with high economic importance and supply risk. In this context, this paper aims to develop a conceptual methodology to identify CRMs in Turkey. The methodology integrates a multi-criteria decision-making method (MCDM) to provide the raw material criticality matrix regarding various criteria, the EU (European Union) method, which represents supply risk and economic importance indicators, and the time series analysis method, in which dynamic evaluation of materials over time instead of the static indicators. We first provide a Bayesian Best-Worst method (B-BWM) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) based model for the criticality matrix, which enables evaluations of participated experts to be combined to reveal the weights of the criteria and sub-criteria from a probabilistic point of view without loss of knowledge. The main and sub-criteria include supply risk and economic importance, which are frequently studied in the literature, but also environment, price, secondary production, and socio-economic indicators are evaluated in the criticality matrix. Then, exponential smoothing forecast, one of the Time Series Analysis models, which determine the element criticality in the perspective of future years with the data of import figures of Turkey, is superior to the other models. Finally, with some modifications, the EU criticality methodology is used to quantify the raw materials regarding each material associated with the sector applications and their value-added and supply disruptions. Thus, a comprehensive criticality list integrating the results of the three mentioned methods is important because Turkey's raw materials characterize many sectors. The findings should also interest practitioners and researchers as the detailed assessment of raw material criticality ensures a sufficient database for future studies.
AtıfScopus24WoS14İncele - MakaleYalnız künye2017PROJECT MANAGEMENT IN HEALTHCARE: A CASE STUDY FOR PATIENT FLOW EVALUATION IN AN EMERGENCY ROOM USING FUZZY CPM AND FUZZY PERT
Gül, Muhammet; Güneri, Ali Fuat; Günes, Gizem
An ideal healthcare system is considered as a system that provides the most quality service level, lower costs and unlimited access. Any delay in patient flow may result in undesired consequences and losses in healthcare facilities such as hospitals and their sub units. Project management is defined as application of techniques to project activities to meet the project requirements. It has techniques that can help healthcare facilities and units standardize care and quality, reduce costs, improve effectiveness and decrease prolonged waits. The current study is carried out in an emergency department of a university hospital to understand the patient flow of the department with respect to the Fuzzy Critical Path Method (FCPM) and Fuzzy Program Evaluation Review Technique (FPERT). The reason for incorporating fuzzy sets is stemmed from that fuzzy numbers are more effective for high uncertainty processes as in emergency departments. Activities affecting patient flow through the ED are identified and project network is drawn. 1500 patients' data about the times of each activities are obtained from the observed ED. Findings through application of FCPM and FPERT, the expected time for completion of the project, the critical path and slack times are determined.
AtıfWoS2İncele
