22 research outputs found

    A novel network data envelopment analysis model for performance measurement of Turkish electric distribution companies

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    Electric distribution companies have a significant role for both households and industries. Benchmarking of the electric distribution companies in the energy sector has become a subject that is studied widely nowadays due to the effect of privatization policies for developing countries. Since there are multiple production stages regarding the generation and supply procedures of electric power, Network DEA technique is used. Directional Distance Function is also integrated into Network DEA technique. Electric distribution companies are organizations that are aiming at maximizing profit while minimizing the expenses. The main problem is how the profit idea can be integrated into the evaluation process. The aim of the proposed model is to evaluate profit efficiency of electric distribution companies while taking into account expansion cost for additional energy supply. This two stage approach is applied to Turkish electric distribution companies. Results are presented based on radial and profit efficiency measures. The proposed model is demonstrates realistic results by considering the expenses and incomes of distribution companies

    A novel network data envelopment analysis model for performance measurement of Turkish electric distribution companies

    Get PDF
    Electric distribution companies have a significant role for both households and industries. Benchmarking of the electric distribution companies in the energy sector has become a subject that is studied widely nowadays due to the effect of privatization policies for developing countries. Since there are multiple production stages regarding the generation and supply procedures of electric power, Network DEA technique is used. Directional Distance Function is also integrated into Network DEA technique. Electric distribution companies are organizations that are aiming at maximizing profit while minimizing the expenses. The main problem is how the profit idea can be integrated into the evaluation process. The aim of the proposed model is to evaluate profit efficiency of electric distribution companies while taking into account expansion cost for additional energy supply. This two stage approach is applied to Turkish electric distribution companies. Results are presented based on radial and profit efficiency measures. The proposed model is demonstrates realistic results by considering the expenses and incomes of distribution companies

    An optimistic-pessimistic DEA model based on game cross efficiency approach

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    The ranking of the decision making units (DMUs) is an essential problem in data envelopment analysis (DEA). Numerous approaches have been proposed for fully ranking of units. Majority of these methods consider DMUs with optimistic approach, whereas their weaknesses are ignored. In this study, for fully ranking of the units, a modified optimistic–pessimistic approach, which is based on game cross efficiency idea is proposed. The proposed game like iterative optimistic-pessimistic DEA procedure calculates the efficiency scores according to weaknesses and strengths of units and is based on non-cooperative game. This study extends the optimistic-pessimistic DEA approach to obtain robust rank values for DMUs. The proposed approach yields Nash equilibrium solution, thus overcomes the problem of non-uniqueness of the DEA optimal weights that can possibly reduce the usefulness of cross efficiency. Finally, in order to verify the validity of the proposed model and to show the practicability of algorithm, we apply a real-world example for selection of industrial R&D projects. The proposed model can increase the discriminating power of DMUs and can fully rank the DMUs

    A new approach based on regression analysis and mathematical programming to multi-group classification problems

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    WOS: 000472481600019In this study, for solving multi-group classification problems, a new two-stage hybrid classification method based on regression analysis and mathematical programming has been developed. In the first step of the proposed method, the classification score of each unit is estimated with the help of the linear regression equation for each unit. In the second step, the classification of the units is performed by the mathematical programming model based on clustering analysis. The proposed method combines the strengths of regression analysis and mathematical programming method. From the 10 real data sets taken the well-known literature and simulation study results, it is observed that the proposed method outperforms the regression analysis, mathematical programming and artificial neural network based classification methods

    Veri Zarflama Analizi Tabanlı Yeni Bir Hibrid İki Gruplu Sınıflandırma Modeli

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    Bu çalışmada iki gruplu sınıflandırma problemlerinin çözümünde kullanılabilecek yeni bir sınıflandırma modeli geliştirilmiştir. Bu model Veri Zarflama Analizi BCC modeline dayanan Pendharkar ve Troutt (2014) modeli ile Sueyoshi (2004) tarafından önerilen iki aşamalı sınıflandırma modelinin bir karmasıdır. Çalışmanın amacı, BCC modelindeki parçalı doğrusal etkinlik sınırı ve iki aşamalı detaylı inceleme fikri sayesinde iki gruplu sınıflandırma problemlerini ele almaktır. Önerilen yeni yaklaşım Pendharkar ve Troutt (2014)’den alınan bir örnek üzerinde ayrıntılı olarak incelenmiş ve ayrıca yapılan simülasyon çalışmasından önerilen yöntemin sınıflandırma performansının diğer iki yöntemden daha iyi olduğu gözlenmiştir

    A modification of a mixed integer linear programming (MILP) model to avoid the computational complexity

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    Having multiple optimal solutions to weights affects to a great extent the consistency of operations related to weights. The cross efficiency method is the most frequently studied topic in data envelopment analysis (DEA) literature. Originally, the cross efficiency method included the efficiency evaluations that were obtained for a decision making unit (DMU) by the classical DEA for the reuse of optimal weights in other DMUs. As the optimal weights in classical DEA solutions usually have multiple solutions, this reduces the usefulness of the cross evaluation. Lam (J Oper Res Soc 61:134–143, 2010) proposed a mixed-integer linear programming (MILP) formulation based on linear discriminant analysis and super efficiency method to choose suitable weight sets to be used in cross efficiency evaluation. In this study, Lam’s MILP model has been modified to reduce the steps during the solution process. The model also becomes a linear programming model after the modification to make it easier to use and to reduce the computational complexity. Numerical examples indicate that the proposed weight determination model both reduces the steps and minimizes computational complexity. Furthermore, it has similar performance with Lam’s MILP model for the cross efficiency evaluation. © 2015, Springer Science+Business Media New York

    Şehirlerin Suç Türlerine Göre İkili Kümeleme Yöntemi ile Gruplandırılması: Türkiye Örneği

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    Suç bölgelerinin oluşturulması suçlara karşı önlemlerin alınmasında kritik öneme sahiptir. Bu bölgelerin oluşumunda kullanılan geleneksel kümeleme yöntemleri yalnızca tek boyutta kümeleme yaparken, belirli kümeler yerine genel sonuçlar sağlar. Bu çalışmada, ayrıntılı kümelerin oluşturulması için ikili kümeleme (biclustering) yöntemlerinden Bimax algoritmasının uygulanabileceği önerilmektedir. Bu yöntemle, hem suçun işlendiği bölgeler hem de suç türleri aynı anda kümelenerek suç bölgeleri oluşturulmuştur. Bu suç bölgeleri ile ilgili sosyo-ekonomik değişkenler arasındaki farklılıklar analiz edilmiş ve suç bölgelerine özgü özellikler sunulmuştur

    Şehirlerin Suç Türlerine Göre İkili Kümeleme Yöntemi ile Gruplandırılması: Türkiye Örneği

    No full text
    Suç bölgelerinin oluşturulması suçlara karşı önlemlerin alınmasında kritik öneme sahiptir. Bu bölgelerin oluşumunda kullanılan geleneksel kümeleme yöntemleri yalnızca tek boyutta kümeleme yaparken, belirli kümeler yerine genel sonuçlar sağlar. Bu çalışmada, ayrıntılı kümelerin oluşturulması için ikili kümeleme (biclustering) yöntemlerinden Bimax algoritmasının uygulanabileceği önerilmektedir. Bu yöntemle, hem suçun işlendiği bölgeler hem de suç türleri aynı anda kümelenerek suç bölgeleri oluşturulmuştur. Bu suç bölgeleri ile ilgili sosyo-ekonomik değişkenler arasındaki farklılıklar analiz edilmiş ve suç bölgelerine özgü özellikler sunulmuştur
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