ISSN (Print): ISSN Pending

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Editor-in-chief: Ehsan Zanboori

Currrent Issue: Volume 2, Number 1, 2016


A General Form of Fuzzy Linear Fractional Programs with Trapezoidal Fuzzy Numbers

1Department of Mathematics, National Institute of Technology Jamshedpur, India

2Department of Applied Mathematics, Lahijan Branch, Islamic Azad University, Lahijan, Iran

International Journal of Data Envelopment Analysis and *Operations Research*. 2016, 2(1), 16-19
doi: 10.12691/ijdeaor-2-1-3
Copyright © 2016 Science and Education Publishing

Cite this paper:
Sapan Kumar Das, S. A. Edalatpanah. A General Form of Fuzzy Linear Fractional Programs with Trapezoidal Fuzzy Numbers. International Journal of Data Envelopment Analysis and *Operations Research*. 2016; 2(1):16-19. doi: 10.12691/ijdeaor-2-1-3.

Correspondence to: Sapan  Kumar Das, Department of Mathematics, National Institute of Technology Jamshedpur, India. Email:


In this paper, we have been pointed out the study of fuzzy linear fractional programming (FLFP) problems with trapezoidal fuzzy numbers. Where the objective functions are fuzzy numbers and the constraints are real numbers. In this paper a new efficient method for FLFP problem has been proposed, in order to obtain the fuzzy optimal solution with unrestricted variables and parameters. These proposed methods is based on crisp linear fractional programming and newly transformation technique also used. A computational procedure has been presented to obtain an optimal solutions. To show the efficiency of our proposed method a real life example has been illustrated.



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On The Continuous Poisson Distribution

1Mathematics Department, Education College, Al-Mustansiriya University, Baghdad, Iraq

International Journal of Data Envelopment Analysis and *Operations Research*. 2016, 2(1), 7-15
doi: 10.12691/ijdeaor-2-1-2
Copyright © 2016 Science and Education Publishing

Cite this paper:
Salah H Abid, Sajad H Mohammed. On The Continuous Poisson Distribution. International Journal of Data Envelopment Analysis and *Operations Research*. 2016; 2(1):7-15. doi: 10.12691/ijdeaor-2-1-2.

Correspondence to: Salah  H Abid, Mathematics Department, Education College, Al-Mustansiriya University, Baghdad, Iraq. Email:


There are no scientific works deal directly and Extensively with the continuous Poisson distribution (CPD). There are some of rare allusions here and there. In this paper we will take this issue on our responsibility. We consider here the continuous Poisson distribution. Different methods to estimate CPD parameters are studied, Maximum Likelihood estimator, Moments estimator, Percentile estimator, least square estimator and weighted least square estimator. An empirical study is conducted to compare among these methods performances. We also consider the generating issue. Other empirical experiments are conducted to build a model for bandwidth parameter which is used for Poisson density estimation.



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A Stochastic Data Envelopment Analysis Model Considering Variation in Input and Output Variables

1Department of Operations Research and Decision Support, Faculty of Computers and Information, Cairo University, Egypt

2College of Business Administration, American University in the Emirates, United Arab Emirates

International Journal of Data Envelopment Analysis and *Operations Research*. 2016, 2(1), 1-6
doi: 10.12691/ijdeaor-2-1-1
Copyright © 2016 Science and Education Publishing

Cite this paper:
Basma E. El-Demerdash, Ihab A. El-Khodary, Assem A. Tharwat. A Stochastic Data Envelopment Analysis Model Considering Variation in Input and Output Variables. International Journal of Data Envelopment Analysis and *Operations Research*. 2016; 2(1):1-6. doi: 10.12691/ijdeaor-2-1-1.

Correspondence to: Basma  E. El-Demerdash, Department of Operations Research and Decision Support, Faculty of Computers and Information, Cairo University, Egypt. Email:


Data envelopment analysis (DEA) is a nonparametric method in is used to measure the relative efficiency of comparable institutions and also used for benchmarking in operations management. There is a weakness in conventional DEA models that it does not allow uncertainty variations in input and output variables however, in many real life applications variables are usually vague. As a result, DEA efficiency measurement may be sensitive to such variations. Therefore, in this paper, input oriented model is one of the classic models in DEA going to develop in stochastic DEA that allow some of input and output variables have random in nature. Finally, an illustrative example has been presented.



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