Sürdürülebilir Kalkınma Amaçları
Yayınlar
- MakaleYalnız künye2021Scopus SJRQ1Extension of FEMA and SMUG models with Bayesian best-worst method for disaster risk reduction
Yanilmaz, Sumeyye; Baskak, Dilber; Yucesan, Melih; Gul, Muhammet
Turkey is one of the countries that face many natural and man-made disasters. The entire geography of Turkey is affected by these disasters and the secondary disasters resulting from them. Tunceli is located in the Eastern Anatolia Region of Turkey and is a disaster-prone region. Therefore, it is important to carry out an adaptable hazard analysis for the region and support the national disaster risk reduction struggle. In this study, a comprehensive disaster hazard analysis was conducted for Tunceli province, and potential mitigation measures were discussed. As methodological background, FEMA (Federal Emergency Management Agency) and SMUG (Seriousness Manageability Urgency Growth) models, which are well-known methods, were extended under the Bayesian Best-Worst Method (BWM). Bayesian BWM is a pairwise comparison-based multi-criteria decision-making method that takes a probabilistic view of the experts' group decision without losing information, providing less pairwise comparison and higher consistency. Nine different disaster hazards for the Tunceli region are prioritized by the proposed approach. Initially, weights of the risk parameters in FEMA and SMUG and the priority values of disaster hazards based on each parameter were calculated. Then, ranking orders were determined. In addition, more precise evaluations were made for the results obtained with the credal ranking graphs. Some comparative studies were also included in the study to test the solidity of the approach. According to the results, both models showed that the top priority hazard for Tunceli is “earthquake”. Also, flood, mass movement, terrorism, and epidemics are hazards with higher priority to be taken into account. Considering the final preference values of disaster hazards for Tunceli province, the first three hazards for the FEMA model are earthquake with 0.192, mass movement with 0.141 and flood with 0.114, respectively. In the SMUG model, earthquake with 0.194, flood with 0.129 and epidemic disease with 0.120 are in the first three places.
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İncele - MakaleAçık Erişim2020Mekanik tesisat projelerinde best worst ve nötrosofik ahp entegre modeliyle hata türü ve etkileri analizi
Yucesan, Melih
Hata türü ve etkileri analizi (FMEA), sistemlerdeki, tasarımlardaki, ürünlerdeki, projelerdeki veya projelerdeki güvenliği iyileştirmeyi, tanımlamayı, değerlendirmeyi ve en aza indirmeyi hedefleyen bir risk değerlendirme aracıdır. Risk önceliği numarası (RPN), FMEA bazlı risk değerlendirme uygulamaları için temel değerlendirme kriteridir. RPN'in oluşum (O), şiddeti (S) ve tespiti (D) gibi risk faktörlerine dayanarak uygun şekilde hesaplanmalıdır. Bununla birlikte, geleneksel RPN hesaplama yöntemi, risk faktörlerinin ağırlığını göz önünde bulundurmamak gibi birçok nedenden dolayı ağır biçimde eleştirilmiştir. Geleneksel FMEA yönteminin bu dezavantajının üstesinden gelmek için, bu makale, mekanik tesisat projeleri için Best Worst method (BWM) ve Nötrosofik analitik hiyerarşi süreci (NAHP) ile entegre modelini içeren FMEA modelini önermektedir. FMEA parametresi S, O ve D'nin ağırlıkları, BWM yöntemiyle hesaplanır ve bu da, tutarlı bir şekilde ikili karşılaştırma ve güvenilir sonuçlar sağlar. Daha sonra dokuz arıza modu, NAHP metodu ile S, O ve D parametreleri açısından değerlendirilir. Arıza modlarının risk önceliklerini belirlemek için risk öncelik endeksleri hesaplanır. Son olarak, belirlenen arıza modları için önleyici tedbirler önerilmiştir.
AtıfOpenAlex2
İncele - MakaleYalnız künye2020Holding of dam water levels at optimum with fuzzy linear programming when electricity is produced in serried dam lakes
Yucesan, Melih; Kahraman, Gökhan
In this study, the Euphrates river basin in a sequential manner established a scenario modeled after Turkey's three largest hydropower plant was established. In this scenario, according to the needs of the interconnected system, the lake levels of these three dams were kept at the highest possible level and energy was produced. In this way, the maximum level of water, which means energy, is kept and the turbine-generator units are operated at the highest possible efficiency and electricity is produced. The demand for electricity, the minimum and maximum water required in the dams, were handled as turbid. Then, for the determined scenario, the energy required by the interconnected system from these dams is determined from which dam and how many units will work for how long.
- MakaleAçık Erişim2020Scopus SJRQ1Evaluation of hospital disaster preparedness by a multi-criteria decision making approach: The case of Turkish hospitals
Ortiz-Barrios, Miguel; Gul, Muhammet; López-Meza, Pedro; Yucesan, Melih; Navarro-Jiménez, Eduardo
Considering the unexpected emergence of natural and man-made disasters over the world and Turkey, the importance of preparedness of hospitals, which are the first reference points for people to get healthcare services, becomes clear. Determining the level of disaster preparedness of hospitals is an important and necessary issue. This is because identifying hospitals with low level of preparedness is crucial for disaster preparedness planning. In this study, a hybrid fuzzy decision making model was proposed to evaluate the disaster preparedness of hospitals. This model was developed using fuzzy analytic hierarchy process (FAHP)-fuzzy decision making trial and evaluation laboratory (FDEMATEL)-technique for order preference by similarity to ideal solutions (TOPSIS) techniques and aimed to determine a ranking for hospital disaster preparedness. FAHP is used to determine weights of six main criteria (including hospital buildings, equipment, communication, transportation, personnel, flexibility) and a total of thirty-six sub-criteria regarding disaster preparedness. At the same time, FDEMATEL is applied to uncover the interdependence between criteria and sub-criteria. Finally, TOPSIS is used to obtain ranking of hospitals. To provide inputs for TOPSIS implementation, some key performance indicators are established and related data is gathered by the aid of experts from the assessed hospitals. A case study considering 4 hospitals from the Turkish healthcare sector was used to demonstrate the proposed approach. The results evidenced that Personnel is the most important factor (global weight = 0.280) when evaluating the hospital preparedness while Flexibility has the greatest prominence (c + r = 23.09).
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İncele - MakaleYalnız künye2020Scopus SJRQ1A manufacturing failure mode and effect analysis based on fuzzy and probabilistic risk analysis
Gul, Muhammet; Yucesan, Melih; Celik, Erkan
This study proposes an improved failure mode and effect analysis (FMEA) with fuzzy Bayesian Network (FBN) and fuzzy best-worst method (FBWM) to assess failures in plastic production. To eliminate the drawbacks of the classical risk priority number (RPN) computation of FMEA, this approach is developed. Unlike classical RPN, a new parameter hierarchy is constructed, and three sub-parameters are injected into the approach. These parameters are weighted by the aid of FBWM. Hereafter, a fuzzy rule-based system is constructed by incorporating Bayesian Network (BN). Also, a sensitivity analysis is performed to observe the final FMEA score changes in accordance with the change of subjective probability values. Finally, a comparative analysis with two approaches of classical FMEA and FBWM-based FMEA (without a fuzzy rule-based system incorporating BN) is fulfilled. The results of the study are strengthened with the experts’ opinions regarding the importance of failure modes for the final product and the whole system and supported them by experience feedback in the observed facility.
AtıfScopus68WoS59OpenAlex68İncele - Kitap BölümüYalnız künye2020NARX neural networks model for forecasting daily patient arrivals in the Emergency Department
Yucesan, Melih; Mete, Suleyman; Serin, Faruk; Celik, Erkan; Gul, Muhammet
Regarding measuring of service quality at the emergency departments (ED), essential parameters are length of stay (LOS) and waiting times. Patient arrivals, which is related to LOS and waiting times, is hard to forecast and is affected by many parameters. Therefore, authors employed a Nonlinear Autoregressive Exogenous (NARX) model for forecasting of ED arrivals. NARX models are used extensively in many applications that show non-linear and dynamic behavior, but as far as authors know, the NARX method has not yet been used in the forecast of ED arrivals before. In this study, calendar and climatic variables are defined as input parameters. Patient Arrivals is defined as output parameter. A commercial software, MATLAB, was used to train and test the data set. To find the best network architecture Levenberg- Marquardt (LM) and Bayesian Regularization (BR) algorithms, different lags, and number of neurons were tested. R-squared and mean square error (MSE) are used to evaluate the accuracy of the tested networks.
AtıfScopus2OpenAlex4İncele - Kitap BölümüYalnız künye2020A fuzzy decision-making model for the key performance indicators of hospital service quality evaluation
Yucesan, Melih; Mete, Suleyman; Gul, Muhammet; Celik, Erkan
One of the major concerns of the healthcare industry throughout the world is to provide better hospital service quality. Management and delivery of hospital healthcare services are achieved in a competitive environment in Turkey. For this reason, to make better decisions, the services provided by the public and private hospitals should be monitored and evaluated according to the viewpoint of medical stakeholders. This chapter presents a cause-and-effect, decision-making model in evaluating hospital service quality criteria. Since the decision-making process involves the vagueness of human judgments, a combination of fuzzy sets and decisionmaking trial and evaluation laboratory (DEMATEL) is used. Results of the study demonstrate that medical equipment level of the hospital, the attitude of nurses and medical staff to patients, pharmacists' advice on medicine preservation, medical staff with professional abilities, outpatient waiting time for medical treatment, and number and quality of the bathrooms available have more impact on the entire hospital service quality. In conclusion, the proposed approach will contribute to better providing of healthcare services at a higher quality level.
AtıfScopus5OpenAlex5İncele - MakaleYalnız künye2020Scopus SJRQ2Hospital service quality evaluation: an integrated model based on Pythagorean fuzzy AHP and fuzzy TOPSIS
Yucesan, Melih; Gul, Muhammet
Providing better hospital service quality is one of the major concerns of healthcare industry in the world. Since health services in Turkey are provided in a very competitive environment, for making a better choice, the services delivered by the public and private hospitals should be evaluated according to the viewpoint of stakeholders in terms of satisfaction. In this study, a model proposal is presented based on the concept of Pythagorean fuzzy analytic hierarchy process and Pythagorean fuzzy technique for order preference by similarity to ideal solution method to provide an accurate decision-making process for evaluating the hospital service quality. We study under fuzzy environment to reduce uncertainty and vagueness, and use linguistic variables parameterized by Pythagorean fuzzy numbers. The proposed approach is separated from others with the integration of the methods in a way providing a systematic fuzzy decision-making process. A case study including 32 service quality criteria and two public and one private hospitals in Turkey assessed by 32 evaluators by medical staff, hospital executives, auxiliaries, and patients is performed to demonstrate the applicability and validity of the proposed approach. On conclusion, integrated model produces reliable and suggestive outcomes better representing the vagueness of decision-making process.
AtıfScopus164WoS132OpenAlex190İncele - MakaleYalnız künye2020Scopus SJRQ2A multi-method patient arrival forecasting outline for hospital emergency departments
Yucesan, Melih; Gul, Muhammet; Celik, Erkan
Patient arrivals at the emergency department (ED) of hospitals has an unpredictable behavior. So that, adequate forecasting of this process can serve a management baseline to better allocate ED human resources and medical equipment. In this paper, a multi-method patient arrival forecasting outline for EDs is developed. The methods followed within this study include single methods as linear regression (LR), autoregressive integrated moving average (ARIMA), artificial neural network (ANN), exponential smoothing and hybrid methods as ARIMA–ANN and ARIMA-LR. As the subject of the study, a private hospital ED case in Turkey is carried out. Data of ED patient arrivals for the year of 2016 was used to set up models. Forecasting performance of the multi-method outline was measured using mean absolute percentage error. The ARIMA–ANN hybrid model is shown to outperform in terms of forecasting accuracy. In order to contribute to the current knowledge, this paper is a novel attempt of applying these methods to model ED patient arrivals and making an overall assessment among them. The results can be used to aid in strategic decision-making on ED staffing and scheduling policy planning in response to predictable arrival variations.
AtıfScopus29WoS26OpenAlex37İncele - MakaleYalnız künye2019Green Supplier selection for plastic industry using integrated model based on Pythagorean fuzzy AHP and fuzzy TOPSIS
Yucesan, Melih
Purpose –Supply Chain Management (SCM) has emerged in recent years and is now increasing in popularity. It aims to reduce production costs, maximize earnings, improve customer relations, improve inventory management and increase customer satisfaction. Reducing total cost of procurement is one of the most important parameters in aligning the objectives of partners in a supply network.Design/methodology/approach – This paper proposed Pythagorean Fuzzy Analytic Hierarchy Process (PFAHP) and Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) integrated model for green supplier selection for plastic industry. In the first phase of the study, the parameters to be used in selecting suppliers are determined. Then, by making pairwise comparisons, the weights of these parameters are determined with PFAHP method. Finally, the supplier that is most suitable for 3 suppliers is determined using the FTOPSIS method.Findings – Among the criteria evaluated by 5 experts, the most important criteria, the parameters of the Inspection methods and management and organizations are determined as the most important parameters respectively. The supplier no. 3 has been identified as the most suitable supplier.Discussion –The case study is performed under a fuzzy environment to reduce uncertainty and vagueness, and linguistic variables parameterized by interval-valued Pythagorean and triangular fuzzy numbers are used. Through the case study, 8 main and 45 sub-criteria supplier selection evaluation criteria used to assess 3 suppliers by FTOPSIS. However, our study has some disadvantages and possible further work is recommended. Other possible different fuzzy sets can be used in the projected method.
AtıfTR Dizin3İncele - MakaleYalnız künye2019A Fuzzy Goal Programming Model Based on MINIMAX Approach for Solving Multi Product ProductionPlanning Problems
Yucesan, Melih; Zengin, Hilmi
In this study, a production plan proposal is made for a company that produces furniture using fuzzygoal programming (FGP) and aim to reach Produce amount and profit goal of the decision maker.These goals were determined to be fuzzy because they cannot be determined precisely. In theproposed model, the number of workers in each section has been rearranged. In the case of using theproposed model, it was suggested that the company could continue its activities by using 8% lessworkers than in the previous period and the production departments would work more efficiently.
- MakaleYalnız künye2019Scopus SJRQ1Risk evaluation and prevention in hydropower plant operations: A model based on Pythagorean fuzzy AHP
Yucesan, Melih; Kahraman, Gökhan
Hydropower generation facilities are becoming increasingly popular in many parts of the world. One of the main reasons for this situation is that the resource reserves such as coal, petroleum and natural gas, which are called conventional energy sources, decrease day by day and their prices rise. So the efficient operation of hydroelectric power plants has become very important. When these plants are operated, it is possible to cause many hazards, including injury, illness, death, damage to the environment, property and equipment. In this study, it is aimed to perform risk assessment for hydroelectric power plants using Pythagorean fuzzy Analytical hierarchy process (PFAHP) method. The team of experts has identified twenty hazards and their results that could occur in the operation of the hydroelectric power plant. The weights of the hazards were determined by using linguistic expressions. Preventive measures have been taken for the three most important hazards. The results of this study are expected to contribute to the safety of hydropower plants and the prevention of financial losses.
AtıfScopus143WoS123OpenAlex147İncele - Derleme MakaleAçık Erişim2019Stochastic multi-criteria decision-making: an overview to methods and applications
Celik, Erkan; Gul, Muhammet; Yucesan, Melih; Mete, Suleyman
Background: The alternatives selection problem with multi-criteria in stochastic form variables is called as stochastic multi-criteria decision-making. The stochasticity of the criteria is considered using stochastic dominance, prospect theory, and regret theory. Main text: In this paper, a total 61 papers are reviewed and analyzed based on method(s) used in stochastic multi-criteria decision-making problem, method used in stochasticity, specific objective, application area, and so on classification. All papers with respect to classification aspects are examined their real or empirical applications. Moreover, the studies are statistically investigated to present the latest trends of stochastic multi-criteria decision-making. Conclusions: This detailed review study ensures a comprehension for researchers on stochastic multi-criteria decision-making in respect of showing up-to-date literature and potential research areas to be concentrated in the future. It is observed that the stochastic multi-criteria decision-making problem has an attractive approach by researchers.
AtıfScopus19WoS15OpenAlex19İncele - MakaleYayıncıda açık erişim2019Scopus SJRQ3An integrated best-worst and interval type-2 fuzzy TOPSIS methodology for green supplier selection
Yucesan, Melih; Mete, Suleyman; Serin, Faruk; Celik, Erkan; Gul, Muhammet
Supplier selection is one of the most important multi-criteria decision-making (MCDM) problems for decision-makers in the competitive market. Today's organizations are seeking new ways to reduce the negative effects they have on the environment and to achieve a greener system. Currently, the concept of green supplier selection has gained great importance for its ability to incorporate environmental or green criteria into classical supplier selection practices. Therefore, in this study, a multi-phase MCDM model based on the best-worst method (BWM) and the interval type-2 fuzzy technique for order preference by similarity to ideal solution (IT2F TOPSIS) is proposed. A case study in a plastic injection molding facility in Turkey was carried out to show the applicability of the proposed integrated methodology. The paper offers insights into decision-making, methodology, and managerial implications. Results of the case study are examined and suggestions for future research are provided.
AtıfScopus93WoS85OpenAlex98İncele - MakaleAçık Erişim2018Sales Forecast with YSA, ARIMA and ARIMAX Methods: An Application in the White Goods Sector
Yucesan, Melih
The white goods sector is one of the locomotive sectors of the country due to the contributions of employment and exports. The technological developments and globalization experienced in recent years are among the sectors that are affected by the changing and competitive conditions. Efficient production planning; must meet the current demand in time and with minimal cost. Determining the current demand is possible with a good sales forecast. In this sense, sales forecasting plays an important role in the success of decision makers. In this study, the sales forecast model for the white goods sector was proposed. The 46 months’ sales data have been used for dishwashers, refrigerators, small house appliances and televisions. The exchange rate, holiday days, consumer confidence index, producer price index, housing sales in the region are used as explanatory variable. It can be said that the most accurate estimates are obtained by using the ANN method when mean squared error (MSE) compared which is the performance criterion.
AtıfOpenAlex5TR Dizin6İncele - MakaleYalnız künye2018Forecasting Monthly Sales of White Goods Using Hybrid Arimax and Ann Models
Yucesan, Melih
In this study, hybrid ARIMAX-ANN and SARIMAX-ANN sales forecasting modelsare proposed for a white goods wholesaler. White goods industry which is one of the durable goodssub-sector includes washing machines, dishwashers, refrigerators and small home appliances. Inmaking forecasts, 46-month sales data of a white goods wholesaler are used. Factors influencingsales such as exchange rate, holidays, consumer confidence index (CCI), producer price index(PPI) and residential sales of the region are used as explanatory variables. The study contributesto the current literature by some aspects. First, there is no attempts applying the ARIMAX-ANNand SARIMAX-ANN hybrid models to forecast sales data in white goods industry. Second, thehybrid models combine the advantages of times series and ANN models. ARIMAX models areinsufficient to solve complex nonlinear problems. On the other hand, ANN is sufficient to explainnonlinear relationships. On conclusion, use of hybrid models can increase the accuracy of themodels.
- MakaleAçık Erişim2018Scopus SJRQ3Performance comparison between ARIMAX, ANN and ARIMAX-ANN hybridization in sales forecasting for furniture industry; [Usporedba performansi modela ARIMAX, ANN i hibridizacije ARIMAX-ANN u predviđanju prodaje za industriju namještaja]
Yucesan, Melih; Gul, Muhammet; Celik, Erkan
Manufacturing firms aim to increase their profits and reduce costs in a competitive and rapidly changing market. One of the most important ways to reach these goals is to forecast sales correctly. Furniture manufacturing, which is considered a prosperous and growing industry in Turkey, has an increasing trend related to the growth in construction and associated industries, increase in urban migration and increase in per capita income. Accuracy of sales forecasting in furniture industry is affected by external factors, such as consumer confidence index, producer price index, month of the year and number of vacation days as well as the time factor itself. This study aims to develop an Autoregressive Integrated Moving Average with external variables (ARIMAX) to forecast the total monthly sales of furniture products of a well-known manufacturer in Turkey. As a follow up study, a performance comparison between ARIMAX, artificial neural networks (ANNs) and ARIMAX-ANN hybridization is performed. In conclusion, results of performance measures demonstrate that hybrid model developed for each amount of product sales give better accuracy values than single methods. Overall, it is proved that using the ARI-MAX and hybridization of this method with ANN are applicable for forecasting monthly sales of furniture products.
AtıfScopus7WoS5OpenAlex20İncele - MakaleYalnız künye2017Çekyat ÜretimindeÖncelikli Hedef Programlama İle Bütünleşik Üretim Planlaması
Yucesan, Melih
Bu çalışmanın amacı, mobilya endüstrisinde çekyat üretimi yapan bir işletmenin bütünleşik üretim planlama faaliyetleri için öncelikli hedef programlama yaklaşımının kullanılabilirliğini göstermektir. Karar verici için iki farklı bütünleşik üretim planı önerisi yapılmıştır. Planlardan biri iki öncelikli hedef programlama modeli kullanılarak yapılan bütünleşik üretim planıdır. Birinci öncelik hedeflenen kar miktarıdır, ikinci öncelik ise hedeflenen üretim miktarı ve hat düzgünleştirmedir. Birinci ve ikinci planda aynı kar miktarı hedeflenmesine rağmen, ikinci planda iş istasyonlarının çalışma süreleri mümkün olduğunca yakın olması istenmiştir. Böylece iş istasyonlarının boşta bekleme süreleri azalacaktır. Yapılan bu çalışma sonucunda üretim planlama ve kontrol faaliyetlerinin işletme verimliliği üzerindeki önemi ortaya koyulmuştur. Önerilen üretim planı modeli esas alınarak gelecek dönemlerde, model üzerinde ürün sayısı, çeşidi ve planlama dönemi sayısı değiştirilerek farklı amaçlar doğrultusunda farklı sonuçlar elde edilebileceği önerilmektedir
AtıfTR Dizin1İncele - MakaleYalnız künye2017An Efficiency Evaluation Model for Academic Faculties of a Leading University by Data Envelopment Analysis
Gul, Muhammet; Yucesan, Melih; Duman, Onur
Data envelopment analysis (DEA) is a linear programming based data analytic method for measuring the relative efficiency of organisational units where the presence of multiple inputs and outputs makes comparisons difficult. Academic departments have critical importance for a university so we agree to research and compare about academic faculties in a leading university in Turkey. The aim of the study is to measure the relative efficiency of the academic faculties and determine the efficient/inefficient ones in the studied university. 12 faculties of the university are investigated within the scope of this study. The input variables are considered as total number of academic staff, total number of non-academic staff, number of students and the output variables are as number of publications, number of projects and the percentage of budget used. While results of CCR model show an average of 90.5% relative efficiency value, five faculties are found 100% efficient according to the CCR model. According to BCC model, the results have an average of 93.7% and 6 faculties are 100% efficient. In terms of the potential improvements evaluated for each inefficient faculty, it is seen that faculty of mechanical engineering and faculty of civil engineering are the ones requiring the most improvement. This paper contributes to the literature a lot however it is a new and proper study on efficiency analysis of faculties of a Turkish university. On conclusion of the DEA efficiency scores, the existence of misallocation of resources or/and inefficient applications to the faculties' academic development are uncovered.
- MakaleAçık Erişim2017Scopus SJRQ3Application of artificial neural networks using bayesian training rule in sales forecasting for furniture industry; [Primjena umjetnih neuronskih mreža uz pomoć Bayesova pravila učenja u predviđanju prodaje za industriju namještaja]
Yucesan, Melih; Gul, Muhammet; Celik, Erkan
Most organizations in manufacturing environments aim to increase their profits and reduce costs against competitive and rapidly changing market conditions. Accuracy of sales forecasting is undoubtedly a successful way to reach the aforementioned goals. At the same time, this enables executives to improve customer satisfaction, reduce lost sales and plan production efficiently. As a growing industry in Turkey, furniture manufacturing has an increased product demand in relation to the recent growth in construction and related industries, increase in urban population and increase in person-level income. Therefore, accurate sales forecasting systems in this industry are more focused on the special and calendar factors, such as consumer confidence index, producer price index, time of the year and number of vacation days. In this paper, an artificial neural network (ANN) based forecasting model is proposed by using MATLAB for processing total monthly sales data of a corporate furniture manufacturer located in the Black Sea region of Turkey. The method is a component of ANN, namely Bayesian regularization. The proposed model is applied to monthly sales figures of a corporate furniture manufacturing company. In conclusion, the results of performance measures show that using the ANN model based on Bayesian rules training is an applicable choice for forecasting of monthly sales of the observed furniture factory.
AtıfScopus14WoS11İncele