Sürdürülebilir Kalkınma Amaçları
Yayınlar
- 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.
AtıfScopus5OpenAlex5
İncele - MakaleAçık Erişim2020Scopus SJRQ2An integrated approach of best-worst method (bwm) and triangular fuzzy sets for evaluating driver behavior factors related to road safety
Moslem, Sarbast; Gul, Muhammet; Farooq, Danish; Celik, Erkan; Ghorbanzadeh, Omid; Blaschke, Thomas
Driver behavior plays a major role in road safety because it is considered as a significant argument in traffic accident avoidance. Drivers mostly face various risky driving factors which lead to fatal accidents or serious injury. This study aims to evaluate and prioritize the significant driver behavior factors related to road safety. In this regard, we integrated a decision-making model of the Best-Worst Method (BWM) with the triangular fuzzy sets as a solution for optimizing our complex decision-making problem, which is associated with uncertainty and ambiguity. Driving characteristics are different in different driving situations which indicate the ambiguous and complex attitude of individuals, and decision-makers (DMs) need to improve the reliability of the decision. Since the crisp values of factors may be inadequate to model the real-world problem considering the vagueness and the ambiguity, and providing the pairwise comparisons with the requirement of less compared data, the BWM integrated with triangular fuzzy sets is used in the study to evaluate risky driver behavior factors for a designed three-level hierarchical structure. The model results provide the most significant driver behavior factors that influence road safety for each level based on evaluator responses on the Driver Behavior Questionnaire (DBQ). Moreover, the model generates a more consistent decision process by the new consistency ratio of F-BWM. An adaptable application process from the model is also generated for future attempts.
AtıfScopus96WoS83OpenAlex93
İncele - MakaleAçık Erişim2020Scopus SJRQ3An exhaustive review and analysis on applications of statistical forecasting in hospital emergency departments
Gul, Muhammet; Celik, Erkan
Emergency departments (EDs) provide medical treatment for a broad spectrum of illnesses and injuries to patients who arrive at all hours of the day. The quality and efficient delivery of health care in EDs are associated with a number of factors, such as patient overall length of stay (LOS) and admission, prompt ambulance diversion, quick and accurate triage, nurse and physician assessment, diagnostic and laboratory services, consultations and treatment. One of the most important ways to plan the healthcare delivery efficiently is to make forecasts of ED processes. The aim this study is thus to provide an exhaustive review for ED stakeholders interested in applying forecasting methods to their ED processes. A categorisation, analysis and interpretation of 102 papers is performed for review. This exhaustive review provides an insight for researchers and practitioners about forecasting in EDs in terms of showing current state and potential areas for future attempts.
AtıfScopus63WoS54OpenAlex80
İncele - BildiriYalnız künye2020A risk assessment approach using both stochastic data and subjective judgments
Mete, Suleyman; Oz, Nurdan Ece; Gul, Muhammet; Serin, Faruk; Celik, Erkan; Kahraman, C.; Cevik Onar, S.; Oztaysi, B.; Sari, I.U.; Cebi, S.
Risk assessment describes the overall process regarding identifying hazards and risk factors that have the potential to cause harm, analyzing and evaluating the risk associated with that hazard and determining appropriate ways to eliminate the hazard or control the risk. In the literature, lots of approaches are proposed to prioritize hazards and associated risks quantitatively. Fuzzy sets-based multi-criteria decision-making approaches are forefront that they have the ability in expressing the risks verbally based on decision-maker’s opinions and judgments. MCDA-based risk assessment approaches explain different types of uncertainties, which are generally modeled using stochastic analysis or fuzzy sets. The stochastic analysis is more suitable in modelling the probabilistic uncertainty. Therefore, in this study, a risk assessment approach using both stochastic data and subjective judgments is proposed, and a case study is also performed in a construction project. The VIKOR method is extended and a new risk assessment approach is developed where part of the data is stochastic. A three-year data is used to determine a fitted probability distribution of respected frequency. Evaluation of risks with respect to severity and probability parameters are then made by subjective judgments. In conclusion, a risk prioritization and potential action plan suggestion is performed.
AtıfScopus2OpenAlex3İncele - 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 - MakaleAçık Erişim2019Doğal afet durumu için cbs tabanlı maksimum kapsama yerleşim modeli: tunceli örneği
Celik, Erkan; Özceylan, Eren; Mete, Süleyman; Özkan, Barış
Afet zamanlarında insani lojistik açısından afetzedelerin barınma yerlerine erişimi önemli bir problemdir. İnsani lojistik yönetiminin önündeki en büyük zorluklardan biri de fazla sayıdaki afetzedelerin koordinasyonudur. Özellikle, olay mahallindeki mekânsal verinin eksikliği etkin bir planlamanın önündeki en büyük engellerden biridir. Bu çalışmada, afet zamanlarında kullanılmak üzere potansiyel afetzedelerin ilgili barınaklara atanması için Coğrafi Bilgi Sistemi (CBS) tabanlı bir çözüm yaklaşımı önerilmiştir. Ulaşılan afetzede sayısını maksimize etmek için ArcGIS’in maksimum kapsama yerleşim modeli kullanılmış ve Tunceli ili üzerinde test edilmiştir. Tunceli şehir merkezindeki 2.121 adet binaya 31.076 kişi, nüfus olarak atanmış ve 5 barınma merkezi ile model çalıştırılmıştır. Daha sonra farklı sayıda barınma merkezi ve kapsama alanları altında senaryo analizleri gerçekleştirilmiş ve sonuçlar yorumlanmıştır. Elde edilen sonuçlar, önerilen modelin afetzedelerin barınma merkezlerine atanmasında etkin bir araç olduğunu göstermiştir.
AtıfOpenAlex4TR Dizin2
İncele - MakaleYalnız künye2019Scopus SJRQ1Supply-driven rebalancing of disassembly lines: A novel mathematical model approach
Mete, Suleyman; Çil, Zeynel Abidin; Celik, Erkan; Ozceylan, Eren
In recent years, the interest of disassembly line has increased owing to the economic reasons and increase of environmental awareness. The balancing of the disassembly line is one of the factors affecting directly the performance of the process. Companies with a line used effectively can gain many advantages in terms of economic aspect and it facilitates competition the companies with others. Moreover, uncertainties end-of-life products characteristics and quantity of supply/demand causes reassigned of task and altering cycle time. Rebalancing of disassembly line is required in this situation. In this study, a novel mixed integer programming model is proposed. Firstly, disassembly line balance is created, and then according to the given new supply, tasks are reselected and reassigned to the workstations. A real case study is presented. The generated test problems are also analyzed using proposed mathematical model. Through the analysis of rebalancing the existing disassembly line, it has been identified that an existing balance might have been changed to accommodate changes in the desired output rate in order to cope up with the variation of the cycle time.
AtıfScopus31WoS27OpenAlex31İncele - Derleme MakaleAçık Erişim2019Scopus SJRQ2ANN and ANFIS Approaches to Calculate the Heating and Cooling Degree Day Values: The Case of Provinces in Turkey
Işık, Erdem; İnallı, Mustafa; Celik, Erkan
Energy analysis plays a vital role in developing an optimum and cost-effective design for the heating, ventilating and air conditioning system of a building. The values of heating degree days (HDD) and cooling degree days (CDD) are used to analyze the demand for energy for buildings. In this study, the HDD and CDD values for Turkey were calculated using estimated temperature values. An artificial neural network (ANN) and an adaptive network-based fuzzy inference system (ANFIS) were applied for the estimation of temperature values. The Levenberg–Marquardt training algorithm was used for the feedforward backpropagation of the ANN, whereas the Sugeno-type fuzzy inference system was used for the ANFIS. Meteorological data from the last 11 years were used for the proposed approaches, and these were applied to different stations (n = 50) of the Turkish State Meteorological Service. In relation to the insulated building design, base temperatures have been considered as 16 °C and 18 °C for the HDD and 22 °C and 24 °C for the CDD based on a literature review. Two novel maps were prepared for the CDD and HDD. The calculated degree days and the maps are consistent with those from the Turkish State Meteorological Service.
AtıfScopus13WoS13OpenAlex18İncele - MakaleAçık Erişim2019Scopus SJRQ1An interval type-2 fuzzy QUALIFLEX approach to measure performance effectiveness of ballast water treatment (BWT) system on-board ship
Demirel, Hakan; Akyuz, Emre; Celik, Erkan; Alarcin, Fuat
Ballast water is of paramount importance for safe and efficient shipping operation since it provides ship’s strength and stability. The ballast water, on the other hand, poses serious marine ecological problems due to the non-indigenous species (NIS) carried in sea water. The International Maritime Organisation introduced International Convention for the Control and Management of Ships’ Ballast Water and Sediments (BWM Convention) to prevent the spread of harmful species from one region to another via ballast water. According to the convention, each ship must be equipped with a proper ballast water treatment system (BWTS). In this context, this paper is aimed at measuring the performance effectiveness of current BWTS used in ships. To achieve this purpose, a Qualitative Flexible (QUALIFLEX) method is used under interval type-2 fuzzy sets (IT2FSs) environment. While the QUALIFLEX handles all possible permutations of the alternatives for outranking, the IT2FSs deal with uncertainty this paper provides practical benefits to ship owners, ship’s safety inspectors, managers and marine environmentalists during decision-making progress of the BWTS settlement on-board ship.
AtıfScopus25OpenAlex28İncele - 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 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 künye2018Scopus SJRQ2Fuzzy rule-based Fine–Kinney risk assessment approach for rail transportation systems
Gul, Muhammet; Celik, Erkan
Rail transportation is one of the most crucial public transportation types for big and crowded cities. In rail transportation systems, stakeholders face serious issues involved in workshops, stations, lines and their environments, and general office buildings. In order to reach an increased awareness and better occupational health and safety (OHS) management, a new risk assessment approach is proposed in this study. This approach includes a combination of Fine–Kinney method and a fuzzy rule-based expert system. It captures nonlinear causal relationships between Fine–Kinney parameters. Since there is a high level of vagueness involved in the OHS risk assessment data, the rule-based expert system is developed for probability (P), exposure (E), and consequence (C) for evaluating risk score. A case study is carried out in a rail transportation system in Istanbul/Turkey, and a comparison with the classical Fine–Kinney method is discussed. Results of the case study reveal risk clusters and corresponding control measures that should be taken into consideration. The study methodologically contributes to risk assessment in the knowledge, while case study in a real rail transportation system offers an insight into public transport industry in safety improvement.
AtıfScopus81WoS71OpenAlex86İncele - MakaleAçık Erişim2018Scopus SJRQ1A practical application of human reliability assessment for operating procedures of the emergency fire pump at ship
Akyuz, Emre; Celik, Erkan; Celik, Metin
This paper aims to conduct a practical application for human reliability assessment during operating procedures of an emergency fire pump on-board ship. A systematic human error prediction is performed for designated tasks during operational procedures of the emergency fire pump since human error can be regarded as one of the major factors contributing accidents at sea. Hence, human reliability performance is evaluated to enhance fire safety management in operational level on-board ship. In the paper, marine-specific error producing conditions are adopted under fuzzy sets environment. To enhance consistency of research and minimise subjectivity during expert's judgement stage, the paper is supported with a dominance factor which is used to adjust the impact level of expert's judgments in the aggregation stage of the methodology. The outcomes of the paper provide valuable contributions to the safety managers and technical superintends to monitor fire safety management and crew reliability performance.
AtıfScopus44WoS38OpenAlex42İncele - MakaleYalnız künye2018Scopus SJRQ1A quantitative risk analysis by using interval type-2 fuzzy FMEA approach: the case of oil spill
Akyuz, Emre; Celik, Erkan
Risk assessment in maritime domain is one of the most cited topics since maritime transportation poses potential hazard for human life, marine environment and property. To mitigate risk and enhance safety awareness in maritime transportation, safety researchers have been seeking proactive solutions. This article prompts a quantitative risk-based approach combining interval type-2 fuzzy sets (IT2FSs) with failure mode and effect analysis (FMEA) to perform a comprehensive risk analysis. Thus, potential failure modes and their effects are revealed by calculating risk prioritisation numbers (RPNs). Whilst the FMEA method provides a robust risk analysing tool with relevant control options, the IT2FSs deals with ambiguity and vagueness of linguistic assessment of decision-makers through the FMEA. Hence, expert’s linguistic assessment in risk assessment can be transformed into useful information in terms of enhancing safety and pollution prevention in maritime industry. To demonstrate the proposed approach, potential failures and effects of a real shipboard oil spill case are handled. The findings show that incomplete information exchanged with local maritime authorities, malfunction of oil skimmer and poor organization of shoreline clean-up team are the most important failures during case of oil spill. The proposed approach provides not only theoretical insight into the maritime transportation industry but also practical contributions to chemical/oil tanker safety and environmental protection by mitigating risk in terms of technical or operational aspects.
AtıfScopus95WoS80OpenAlex92İncele - MakaleAçık Erişim2018Scopus SJRQ2The role of human factor in maritime environment risk assessment: A practical application on Ballast Water Treatment (BWT) system in ship
Akyuz, Emre; Celik, Erkan
The role of human factor plays a critical role in the safe and clean operation of maritime industry. Human error prediction can be beneficial to assess risk in maritime industry since shipping activities can pose potential hazards to human life and maritime ecology. The aim of this paper is to propose a risk assessment tool by considering the role of human factor. Hence, the desired safety control level in maritime transportation activities can be ascertained. In the proposed approach, a Success Likelihood Index Method (SLIM) extended with fuzzy logic is used to calculate human error probability (HEP). Severity of consequences are adopted in the proposed approach to assess risk. The quantitative risk assessment approach under fuzzy SLIM methodology will be applied to a very specific case on-board ship: Ballast Water Treatment (BWT) system. In order to improve consistency of research and minimize subjectivity of experts' judgments, the paper adopts the dominance factor which is used to adjust the impact level of experts' judgments in the aggregation stage of the methodology. The paper aims at not only highlighting the importance of human factor in maritime risk assessment but also enhancing safety control level and minimizing potential environmental impacts to marine ecology.
AtıfScopus57WoS52OpenAlex57İncele - MakaleYalnız künye2018Scopus SJRQ1An interval type-2 fuzzy AHP and TOPSIS methods for decision-making problems in maritime transportation engineering: The case of ship loader
Celik, Erkan; Akyuz, Emre
Duration of cargo operation (loading or discharging) is of paramount importance for ship owners and port managers since idle time at terminal significantly boost to the cost of providing shipping service. Hence, it is important to choose the appropriate shiploader type for handling bulk materials. This paper aims to present a comprehensive multi-criteria decision making (MCDM) method extended by interval type-2 fuzzy sets (IT2FSs) for selecting appropriate shiploader type in maritime transportation. The proposed approach incorporates Analytical Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) under IT2FSs environment to overcome more of the uncertainty of experts’ judgement and expression in decision-making. The proposed approach adopts a sensitivity analysis to investigate the impact of key performance indicator (KPI) under numerous conditions. Besides its robust theoretical background, this paper prompts practical benefits to decision-makers (port owners or port managers) who make investment decision for appropriate shiploader type in dry bulk cargo shipment.
AtıfScopus165WoS148OpenAlex172İncele - MakaleYalnız künye2017A stochastic location and allocation model for critical items to response large-scale emergencies: A case of Turkey
Celik, Erkan; Aydin, Nezir; Gumus, Alev Taskin
This paper aims to decide on the number of facilities and their locations, procurement for pre and post-disaster, and allocation to mitigate the effects of large-scale emergencies. A two-stage stochastic mixed integer programming model is proposed that combines facility location-prepositioning, decisions on pre-stocking levels for emergency supplies, and allocation of located distribution centers (DCs) to affected locations and distribution of those supplies to several demand locations after large-scale emergencies with uncertainty in demand. Also,theuseofthemodelisdemonstratedthroughacasestudyfor prepositioning of supplies in probable large-scale emergencies in the eastern and southeastern Anatolian sides of Turkey. The results provide a framework for relief organizations to determine the location and number of DCs in different settings, by using the proposed model considering the main parameters, as; capacity of facilities, probability of being affected for each demand points, severity of events, maximum distance between a demand point and distribution center.
- MakaleYalnız künye2017Estimating Global Solar Radiation for Tunceli City using ANFIS
Celik, Erkan; Gul, Muhammet
Because of the high cost of measurement equipment and their maintenance, global solar radiation measurement is not always implemented. Hence, several forecasting approaches based on fuzzy sets, artificial intelligence or soft computing are proposed to forecast global solar radiation owing to being less cost. However, it is vital to select the most suitable approach for a specific purpose and region. In this study, the adaptive-network based fuzzy inference systems (ANFIS) is proposed to forecast monthly mean daily global solar radiation for Tunceli, Turkey. The monthly data between 1990 and 2010 is used for the proposed approach. The data was obtained from provincial directorate of meteorology of Tunceli. According to the gathered data, the highest value of monthly average daily global solar radiation was measured as 5.218 kWh/m² in the year of 1993. The lowest one with a value of 3.905 kWh/m² belongs to the year of 1997. Similarly, the highest value of monthly average daily sunshine duration was measured as 8.71 hours in the year of 1993. The lowest one with a value of 6.64 hours belongs to the year of 2009. When the data is analysed on a monthly basis, the highest value of monthly average daily global solar radiation was measured as 7.409 kWh/m² in the month of June. The lowest one with a value of 1.762 kWh/m² belongs to the month of December. Similarly, the highest value of monthly average daily sunshine duration was measured as 12 hours in the month of July. The lowest one with a value of 3.1 hours belongs to the month of December. The experiments were applied in MATLAB 7 package software in order to obtain the optimum network architecture. In this network, there are 3 inputs (months, years and monthly average daily sunshine duration) and 1 output (the estimation of the monthly average daily global solar radiation). The ANFIS proposed in this study has Gaussian membership function and twenty fuzzy rules are used. The number of the data points (monthly average daily global solar radiation measurement) is 245. As a performance measure of the ANFIS network, the mean absolute percentage error (MAPE) was used. In testing stage, the MAPE was obtained as 6.365 which is quite well for this type of problem. The coefficient of determination (RSquared) value was calculated as 0.999 which is significantly high. The highly successful results show the success of the fuzzy based methodology of ANFIS which provides estimations of global solar radiation successfully. The presented approach shows that the ANFIS illustrates promising in the forecasting of monthly mean daily global solar radiation using available data. Future studies to estimate the monthly mean global solar radiation of Tunceli city with greater accuracy can be achieved using more apparent meteorological input parameters and different artificial intelligence techniques like artificial neural networks, autoregressive moving average methods or support vector machines. These methods can be improved for available models of daily and hourly estimation of global solar radiation.
AtıfTR Dizin3İncele - BildiriYalnız künye2017Forecasting daily patient visits in an emergency department by ga-ann hybrid approach
Pekel, Engin; Gul, Muhammet; Celik, Erkan; Drobne, S.; Zerovnik, J.; Zadnik Stirn, L.; Kljajic Borstar, M.
An Emergency Department (ED) plays a crucial role in the health system by providing acute care for patients who attend hospital without prior appointment. An accurate forecasting of patient visits in EDs contributes to health care decision makers to better allocate ED human resources and medical equipment. In this paper, a hybrid genetic algorithm–artificial neural network (GA–ANN) approach is developed. The forecasting performance of the hybrid approach is obtained using the real-world data set collected from a public hospital in Istanbul, Turkey. The hybrid GA–ANN model is shown to perform well in terms of forecasting accuracy. In order to contribute to the current knowledge, this paper is a novel attempt of applying GA-ANN to model ED patient arrivals, and the results can be used to aid in strategic decision-making on ED resource planning in response to predictable arrival variations.
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