Sürdürülebilir Kalkınma Amaçları
Yayınlar
- MakaleAçık Erişim2026Scopus SJRQ1Evaluation and Classification of Emergency and Disaster Assembly Areas with ORESTE-Sort
Ozdemir, Umit; Mete, Suleyman; Gul, Muhammet
Emergency and Disaster Assembly Areas (EDAA) are designated safe zones where basic needs can be met until temporary shelters are established following natural or man-made disasters like floods, fires, earthquakes, explosions, or chemical incidents. Promptly relocating disaster victims to these areas is crucial for minimizing loss of life and facilitating effective search and rescue operations by maintaining an uninterrupted flow of information. To prepare for disasters like earthquakes, which cause significant material and emotional damage to large populations, sustainable disaster management must be ensured to evaluate site suitability, correct deficiencies, and avoid inappropriate locations. This study will examine the evaluation criteria for EDAAs established by the Tunceli Provincial Disaster and Emergency Management Authority (AFAD) in terms of area, structure, security, and accessibility, taking into account the region’s specific characteristics. Based on a literature review, eleven criteria have been proposed and ranked using the Besson mean ranking method. Areas have been classified into four categories (e.g., adequate, not suitable) using the optimistic, pessimistic, and comprise approaches of the Assignment Rule Driven by Attitudes (ARDA) and the ORESTE-Sort method. The examination of 19 EDAA provides two perspectives: an optimistic view that recommends classifying eleven areas as first class and using all areas as they are, and a pessimistic view that calls for urgent improvements in three areas and states that one area (EDAA 1) is deemed unsuitable due to its assignment to class (Formula presented.). It is also advised that the second area should not be used, despite being rated as class (Formula presented.), due to its proximity to the river and its slope characteristics. The study also performs a sensitivity analysis of the method and provides recommendations for future research.
AtıfScopus2WoS1
İncele - MakaleAçık Erişim2026Scopus SJRQ4CLASSIFYING VOLUNTEERS PARTICIPATED IN SEARCH AND RESCUE ACTIVITIES: A COMPARATIVE ANALYSIS OF TOPSIS-SORT AND ORESTE-SORT METHODS
Ozdemir, Umit; Mete, Suleyman; Gul, Muhammet
Volunteers collaborate with professionals to provide institutional assistance in various areas; their management differs from that of professionals. To maximise volunteer productivity, categorising volunteers according to their knowledge and experience levels and distributing tasks increases volunteer retention and task efficiency. This study categorizes volunteers into four groups, fulfilling nine criteria identified through a literature review of search and rescue activities. TOPSIS-Sort and ORESTE-Sort (Optimist and Pessimist approaches) are employed in classification. Only one alternative is consistently assigned to the same class across all methods. While ORESTE-Sort offers greater flexibility and three distinct classification outcomes, it is more complex and sensitive to threshold values. TOPSIS-Sort, though simpler and producing a single classification, requires criterion weight. The Wilcoxon signed rank test is applied to evaluate the similarity between ORESTE-Sort and TOPSIS-Sort results; there are significant differences between the two methods. The study concludes by comparing the methods' applications, steps, and solution approaches, highlighting their respective advantages and disadvantages, and suggesting directions for future research.
- MakaleAçık Erişim2026Scopus SJRQ1A two-stage volunteer assignment model for post-disaster search and rescue operations
Ozdemir, Umit; Mete, Suleyman; Gul, Muhammet
Effective volunteer management requires ensuring operational continuity and maximizing benefits from all team members. Prioritizing volunteers with adequate knowledge and experience in task assignments is crucial for maintaining workflow continuity. This study employs a two-stage model for allocating areas and tasks to volunteers in search and rescue operations. The first stage identifies the optimal number of volunteer response centers using the P-median problem. Considering population density as demand, 7 out of 14 accessible and protected disaster collection areas meeting basic needs are selected as optimal response centers based on distance. In the second stage, a mixed-integer programming model is proposed for volunteer assignment, which prioritizes assigning the most knowledgeable and experienced volunteers to critical positions. The model’s flexibility and applicability are demonstrated by incorporating voluntary rest periods, which are allocated based on the urgent needs of response centers in various post-disaster scenarios. Solved using GAMS/CPLEX, the model’s results show that expert volunteers in low-demand scenarios are prioritized, working 5 out of 9 shifts, while other volunteers receive insufficient assignments. In high-demand scenarios, some response centers face volunteer shortages, with a deficit of 62 volunteers across 9 shifts in non-emergency areas. The study evaluates the benefits and drawbacks of the volunteer assignment model and offers recommendations for future research.
AtıfScopus2WoS2OpenAlex3
İncele - MakaleYalnız künye2024Scopus SJRQ1Evaluating sustainability of urban mobility of Asian cities: An integrated approach of interval type-2 fuzzy best-worst method and MULTIMOORA
Yucesan, Melih; Özkan, Barış; Mete, Suleyman; Gul, Muhammet; Özceylan, Eren
The motivation for sustainable urban mobility is driven by the need to create environmentally friendly, socially inclusive, economically viable, and healthier cities for current and future generations. It requires a comprehensive approach that combines infrastructure development, policy changes, behavioral shifts, and technological advancements to transform urban transportation systems. The importance of creating increasingly sustainable urban transportation is now greater than it has ever been. One of the attempts in this field is the sustainable urban transport index (SUTI) developed by the United Nations (UN). Although the SUTI has a comprehensive pool of criteria for the evaluation of mobility sustainability of cities, considering the criteria weights as equal and disregarding the uncertainties present in expert opinions is viewed as a significant drawback. To satisfy the aforementioned deficiency, a novel integrated approach including the best-worst method (BWM), multi-objective optimization by ratio analysis (MOORA) and MOORA plus full multiplicative form (MULTIMOORA) method is develloped and applied for the SUTI evaluation. In order to manage ambiguous linguistic approximations, the utilization of BWM is applied within the framework of interval type-2 fuzzy (IT2F) sets. While IT2F-BWM is used to prioritize the main and sub-indicators of SUTI, MULTIMOORA approach is applied to rank the Asian cities. The findings imply that the proposed approach not only provides a more scientific perspective but also provides the opportunity to perform sensitivity analysis on criteria weights. Therefore, the results obtained in this study are expected to help cities to create a road map for planning sustainable urban mobility (e.g. Sustainable Urban Mobility Plan).
AtıfScopus23OpenAlex26İncele - Kitap BölümüYalnız künye2023Determining the Criterion Weights for the Selection of Volunteers in Humanitarian Organizations by the Best-Worst Method
Ozdemir, Umit; Mete, Suleyman; Gul, Muhammet
Today, it is vital for humanitarian organizations operating in many different fields to select volunteers from the determining criteria according to the needs of the institution. Failure to select volunteers in accordance with the institution's needs may cause the volunteers to be unable to continue their duties and interrupt the institution's work. When choosing volunteers, it is essential for effective volunteer management to classify (expert, experienced, inexperienced, and insufficient) them according to the institution’s needs and assign them starting from the volunteer in the best class volunteer when necessary. The aim of this study is to determine the criteria weights in the classification of volunteers who want to participate in search and rescue activities in humanitarian aid organizations according to the criteria determined before their assignment. In this study, a questionnaire is applied to field experts in Turkey to determine the most important and least important criteria, then criteria weights are calculated by using the Best-Worst Method (BWM). The findings obtained as a result of our study are evaluated and suggestions are made on how to improve it for future studies.
AtıfScopus1OpenAlex1İncele - MakaleYalnız künye2023Scopus SJRQ1An integrated hybrid MCDM approach to evaluate countries’ COVID-19 risks
Mete, Suleyman; Yucesan, Melih; Gul, Muhammet; Ozceylan, Eren
To enable planning and early reaction efforts, it is important to identify the nations most at risk from COVID-19's health and humanitarian effects, which could exceed present national response capabilities. INFORM COVID-19 Risk Index developed by European Commission is one of the initiatives to meet the aforementioned need. However, the Index has 40 conflicting and comprehensive indicators (e.g., health system capacity, hygiene, vulnerability) and different countries that lead to a need for multicriteria decision-making (MCDM) approaches. This paper offers an integrated MCDM approach with two phases to re-assess the countries' COVID-19 risks based on INFORM COVID-19 Risk Index. In the first phase, the 40 indicators are prioritized using the Entropy-based multi-choice best-worst method (MC-BWM) to provide multiple viewpoints for the preferences values. In the second phase, 29 countries from different geographical regions are ranked using the COPRAS (Complex Proportional Assessment) method. Applying these three methods together on the COVID-19 risk assessment of countries is the most significant novelty for the relevant literature. The proposed approach has undergone a thorough comparative evaluation with the released INFORM COVID-19 Risk Index, and recommendations are provided based on different scenario analyses.
AtıfScopus21WoS16OpenAlex18İncele - Kitap BölümüYalnız künye2021Fine–kinney-based occupational risk assessment using interval-valued pythagorean fuzzy vikor
Gul, Muhammet; Mete, Suleyman; Serin, Faruk; Celik, Erkan
This chapter aims at the adaptation of the Fine–Kinney occupational risk assessment concept into the VIKOR multi-attribute decision-making method with an interval-valued Pythagorean fuzzy set. The classical fuzzy set theory has been improved by proposing a number of extended versions. One of them is the Pythagorean fuzzy set. It has been firstly developed by Yager (IEEE Transactions on Fuzzy Systems 22:958–965, [1]). In this chapter, we use this type of fuzzy set with VIKOR since it reflects uncertainty in occupational risk assessment and decision-making better than other fuzzy extensions. To demonstrate the proposed approach applicability, a case study regarding the activities of the surface treatment area in a chrome plating unit of a gun factory is performed. Some additional analysis to test the solidity and validity of the approach is executed. Finally, the Python codes in the implementation of the proposed approach are given for scholars and practitioners for usage in further studies.
AtıfScopus14OpenAlex5İncele - EditoryalYalnız künye2021Preface
Gul, Muhammet; Mete, Suleyman; Serin, Faruk; Celik, Erkan
AtıfScopus2İncele - Kitap BölümüYalnız künye2021Fine–kinney-based occupational risk assessment using interval type-2 fuzzy vikor
Gul, Muhammet; Mete, Suleyman; Serin, Faruk; Celik, Erkan
In this chapter, we improved Fine–Kinney occupational risk assessment approach with interval type-2 fuzzy VIKOR (IT2FVIKOR). VIKOR is a compromise multi-attribute decision-making method proposed by Opricovic (1998). Similar to other compromised solution-based approaches, it considers the solution which is closest to the ideal. In this chapter, we adapted the interval type-2 fuzzy sets (IT2FSs) into VIKOR as it reflects the uncertainty well in decision-making. IT2FVIKOR algorithm under the Fine–Kinney concept provides a useful and solid approach to the occupational health and safety risk assessment. In addition to proposing this new approach, a case study is performed in a gun and rifle barrel external surface oxidation and coloring unit of a gun factory. A validation and a sensitivity analysis is also attached to this study. Finally, the proposed approach is implemented in Python.
AtıfScopus4OpenAlex5İncele - Kitap BölümüYalnız künye2021Fine–kinney-based occupational risk assessment using fuzzy best and worst method (f-bwm) and fuzzy mairca
Gul, Muhammet; Mete, Suleyman; Serin, Faruk; Celik, Erkan
The best-worst method (BWM) proposed by Rezaei (Omega 53:49–57, [1]) is an MCDM method used to achieve the weights of the criteria by making fewer pairwise comparisons and using more consistent decision matrices. In this chapter, instead of crisp numbers, triangular fuzzy numbers that reflect the uncertainty well in real-world problems are used in integration with the BWM method (Guo and Zhao in Knowl Based Syst 121:23–31, [2]) in determining factor weights. Using the fuzzy best and worst method (F-BWM), a model based on Fine–Kinney occupational health and safety risk assessment method was developed for the first time in the literature. Three parameters of Fine–Kinney method are weighted by the mathematical models of F-BWM. Then, the risks are prioritized by fuzzy multi-attribute ideal real comparative analysis (F-MAIRCA). A case study was conducted to demonstrate the feasibility of the approach, and besides this case study, a comparative study was also conducted to test the validity of the proposed approach. This approach led to the conclusion that Fine–Kinney’s method, BWM, MAIRCA, and triangular fuzzy sets make the risk decision-making process more dynamic, taking into account the benefits of these methods individually or in integration.
AtıfScopus11OpenAlex12İncele - Kitap BölümüYalnız künye2021Fine–kinney-based occupational risk assessment using hexagonal fuzzy multimoora
Gul, Muhammet; Mete, Suleyman; Serin, Faruk; Celik, Erkan
Hexagonal fuzzy numbers (HFNs) can be used as a proficient logic to simplify understanding of ambiguity information. HFNs present the usual information in a comprehensive way and also the ambiguity section can be exemplified in a reasonable way. In this chapter, we proposed an improved Fine–Kinney occupational risk assessment approach using a well-known MCDM method Multi-Objective Optimization by Ratio Analysis (MULTIMOORA) using hexagonal fuzzy numbers. Since the mere MULTIMOORA has failed to handle uncertainty and vague information which usually exist in real world problems, we follow integration of HFNs and MULTIMOORA (HFMULTIMOORA). To show the applicability of the novel approach, a case study of risk assessment of a raw mill in cement plant was provided. Comparative analysis with using two aggregation tools as reciprocal rank method and dominance theory are carried out. Finally, the Python implementation of the proposed approach is implemented to be effective for those concerned in the future.
AtıfScopus7OpenAlex5İncele - Kitap BölümüYalnız künye2021Fine–kinney-based occupational risk assessment using intuitionistic fuzzy todim
Gul, Muhammet; Mete, Suleyman; Serin, Faruk; Celik, Erkan
This chapter applies a novel occupational risk assessment approach which merges TODIM with the Fine–Kinney method under the intuitionistic fuzzy set concept. Risk parameters of Fine–Kinney and OHS experts are weighted by an intuitionistic fuzzy weighted averaging (IFWA) aggregation operator. Hence, hazards are quantitatively evaluated and prioritized using the proposed approach. To illustrate the novel risk assessment approach, processes of the gun and rifle assembly line of a factory are handled. A comprehensive risk assessment is carried out to improve operational safety and reliability in the industry. We adapt intuitionistic fuzzy sets in the existing study since they reflect uncertainty with the aid of their membership and nonmembership functions in decision-making better than classical fuzzy extensions. An additional sensitivity analysis by changing the attenuation parameter of TODIM is performed to test the validity of the approach. Finally, the Python codes in the implementation of the proposed approach are given for scholars and practitioners for usage in further studies.
AtıfScopus5OpenAlex9İncele - Kitap BölümüYalnız künye2021Fine–kinney-based occupational risk assessment using single-valued neutrosophic topsis
Gul, Muhammet; Mete, Suleyman; Serin, Faruk; Celik, Erkan
Neutrosophic sets are initially recommended by Smarandache (First international conference on neutrosophy, neutrosophic logic, set, probability, and statistics. University of New Mexico, Gallup, NM, pp 338–353, 2002 [1]). These sets reflect uncertainty and vagueness in real-world problems better than classical fuzzy set theory. It takes into consideration three decision-making situations called indeterminacy, truthiness, and falsity. In Zadeh traditional fuzzy set theory, there is just membership function fuzzy set degree. But, in neutrosophic environment, it considers three membership functions. Unlike intuitionistic fuzzy sets, an indeterminacy degree is considered. In this chapter, we applied a special form of neutrosophic set as single-valued neutrosophic set (SVNs) with the technique for order preference by similarity to ideal solution (TOPSIS) under the concept of Fine–Kinney occupational risk assessment. Since the mere TOPSIS has failed to handle imprecise and vague information which usually exist in real-world problems, we follow the integration of SVNs and TOPSIS. To demonstrate the applicability of the novel approach, a case study of risk assessment of a wind turbine in times of operation was provided. Comparative analysis with some similar approaches and sensitivity analysis by changing the weights of Fine–Kinney parameters are carried out. Finally, the Python implementation of the proposed approach is executed to be useful for those concerned in the future.
AtıfScopus12OpenAlex9İncele - Kitap BölümüYalnız künye2021Fine–kinney occupational risk assessment method and its extensions by fuzzy sets: A state-of-the-art review
Gul, Muhammet; Mete, Suleyman; Serin, Faruk; Celik, Erkan
The Fine–Kinney method (Fine in J Saf Res 3:157–166, 1971; Kinney and Wiruth in Practical risk analysis for safety management. Naval Weapons Center, pp 1–20, 1976), which was first introduced as an occupational health and safety risk analysis tool in the 1970s, is a systematic methodology that provides a mathematical formula for calculating the risk that arises due to a specified hazard. In the traditional version of Fine–Kinney as suggested in its original version, a risk score (RS) is calculated as a result of mathematical multiplication of probability (P), exposure (E), and consequence (C) parameters. These calculated risk scores are used to establish priorities for the corrective efforts in order to eliminate risks or reduce their effects to a reasonable level. This simple and useful method is preferred and implemented by small and medium-sized enterprises. In the academic literature, it has been applied for many risk analysis problems, although it includes several drawbacks recently revealed. In this method, no weight assignment is made for each risk parameter. Also, it is hard to assess consequence, exposure, and probability, precisely. Multi-criteria decision making (MCDM) is a pool of methods used in occupational health and safety risk analysis both by international standard-setting organizations and scholars from the literature. In classical MCDM methods, performance values and weights of decision criteria are known precisely and are specified with crisp numbers. However, many real-world problems contain uncertainties, and the knowledge and judgment of experts cannot be expressed precisely. Fuzzy-based MCDM methods, which are developed to reflect types and degrees of uncertainties better, produce more accurate results compared to classical methods. In this chapter, we first present the basics of Fine–Kinney method, including its implementing procedure, basic terminology, and drawbacks. Then, we provide a state-of-the-art review of Fine–Kinney occupational risk assessment method and its extensions by fuzzy sets. Graphical results obtained from the review are demonstrated to show the current state. Future work suggestions are also included to the chapter to show the possible gaps and possible opportunities.
AtıfScopus12OpenAlex12İncele - Kitap BölümüYalnız künye2021Fine–kinney-based occupational risk assessment using interval type-2 fuzzy qualiflex
Gul, Muhammet; Mete, Suleyman; Serin, Faruk; Celik, Erkan
In this chapter, we improved Fine–Kinney occupational risk assessment approach with interval type-2 fuzzy QUALIFLEX (IT2FQUALIFLEX). QUALIFLEX is an outranking multi-attribute decision-making method proposed by an extension of the Paelinck’s (Pap Reg Sci Assoc 36:59–74,[1]), generalized Jacquet-Lagreze’s permutation method. Similar to other outranking solution-based approaches, it considers the solution which is a comparison of hazards. In this chapter, we adapted the interval type-2 fuzzy sets (IT2FSs) into QUALIFLEX as it reflects the uncertainty well in decision-making. IT2FQUALIFLEX algorithm under the Fine–Kinney concept provides a useful and solid approach to the occupational health and safety risk assessment. In addition to proposing this new approach, a case study is performed in the chrome plating unit. A validation is also performed in this study. Finally, the proposed approach is implemented in Python.
AtıfScopus7OpenAlex7İncele - Kitap BölümüYalnız künye2021Fine–kinney-based occupational risk assessment using interval type-2 fuzzy topsis
Gul, Muhammet; Mete, Suleyman; Serin, Faruk; Celik, Erkan
This chapter proposed an improved Fine–Kinney occupational risk assessment approach using a well-known MCDM method “TOPSIS” under interval type-2 fuzzy set concept. It is defined as a technique for order preference by similarity to ideal solution by Hwang and Yoon [1]. It is based on separation from ideal and anti-ideal solution concept. Since the initial crisp data-based version is insufficient by time in reflecting the uncertainty in decision-maker’s opinions, fuzzy sets are integrated to the TOPSIS algorithm to provide a solid and comprehensive method. Interval type-2 fuzzy set is an improved version of the type-1 fuzzy set. It is also a special version of a general type-2 fuzzy set. Since general type-2 fuzzy systems contain complex computational operations, they cannot be easily applied to real-world problems such as occupational risk assessment. Interval type-2 fuzzy sets are the most frequently used type-2 fuzzy sets due to their ability in handling more uncertainty and producing more accurate and solid results. The Fine–Kinney concept is merged with the interval type-2 fuzzy set concept and TOPSIS for the first time through the literature. To demonstrate the applicability of the proposed approach, a case study is carried out in a chrome plating unit of a gun factory. Some beneficial validation and sensitivity analysis are also performed. Finally, as a creative contribution of our book, the implementation of the proposed approach in Python is performed.
AtıfScopus2OpenAlex3İncele - MakaleYalnız künye2020Scopus SJRQ1A fast branch, bound and remember algorithm for disassembly line balancing problem
Li, Zixiang; Çil, Zeynel Abidin; Mete, Suleyman; Kucukkoc, Ibrahim
In recent years, the interests of disassembly line have increased owing to economic reasons and the increase of environmental awareness. Effective line can provide many advantages in terms of economic aspect and it facilitates competition the companies with others. This study contributes to the relevant literature by a branch, bound and remember algorithm for disassembly line balancing problem with AND/OR precedence. The proposed exact solution method employs the memory-based dominance rule to eliminate the reduplicated sub-problems by storing all the searched sub-problems and to utilise cyclic best-first search strategy to obtain high-quality complete solutions fast. In this paper, minimising the number of stations is taken as the performance measure. The proposed methodology is tested on a set of 260 instances and compared with the mathematical model using CPLEX solver and five well-known metaheuristics. Computational results show that the proposed method is capable of obtaining the optimal solutions for all the tested instances with less than 0.1 seconds on average. Additionally, comparative study demonstrates that the proposed method is the state-of-the-art algorithm and outperforms the CPLEX solver and metaheuristics in terms of both solution quality and search speed aspects.
AtıfWoS66OpenAlex65İncele - KitapYalnız künye2020Computational intelligence and soft computing applications in healthcare management science
Gul, Muhammet; Celik, Erkan; Mete, Suleyman; Serin, Faruk
In today's modernized world, the field of healthcare has seen significant practical innovations with the implementation of computational intelligence approaches and soft computing methods. These two concepts present various solutions to complex scientific problems and imperfect data issues. This has made both very popular in the medical profession. There are still various areas to be studied and improved by these two schemes as healthcare practices continue to develop.
AtıfOpenAlex7İncele - EditoryalYalnız künye2020Preface
Gul, Muhammet; Celik, Erkan; Mete, Suleyman; Serin, Faruk
AtıfScopus1İncele - 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