Probabilistic modelling
S. Abid; R. Abdulrazak
Abstract
In this paper, we introduce a new family of continuous distributions based on [0, 1] Truncated Fréchet distribution. [0, 1] Truncated Fréchet Weibull ([0, 1] ) and [0, 1] Truncated Fréchet ([0, 1] ) distributions are discussed as special cases. The cumulative distribution function, ...
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In this paper, we introduce a new family of continuous distributions based on [0, 1] Truncated Fréchet distribution. [0, 1] Truncated Fréchet Weibull ([0, 1] ) and [0, 1] Truncated Fréchet ([0, 1] ) distributions are discussed as special cases. The cumulative distribution function, the rth moment, the mean, the variance, the skewness, the kurtosis, the mode, the median, the characteristic function, the reliability function and the hazard rate function are obtained for the distributions under consideration. It is well known that an item fails when a stress to which it is subjected exceeds the corresponding strength. In this sense, strength can be viewed as “resistance to failure.” Good design practice is such that the strength is always greater than the expected stress. The safety factor can be defined in terms of strength and stress as strength/stress. So, the [0, 1] strength-stress and the [0, 1] strength-stress models with different parameters will be derived here. The Shannon entropy and Relative entropy will be derived also.
N. Shahsavari pour; M.H. Abolhasani Ashkezari; H. Sheikhi; H. Mohammadi Andargoli; H. Abolhasani Ashkezari
Volume 3, Issue 4 , December 2014, , Pages 1-12
Abstract
Various procedures, methods, constraints and objectives are studied in a flow shop problem during the past decades. In order to adapt the problem to the reality form, its parameters are considered as a fuzzy model. In this problem, we consider the processing time as the trapezoidal fuzzy numbers. The ...
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Various procedures, methods, constraints and objectives are studied in a flow shop problem during the past decades. In order to adapt the problem to the reality form, its parameters are considered as a fuzzy model. In this problem, we consider the processing time as the trapezoidal fuzzy numbers. The purpose of this problem is to find an optimum sequence in a way that the makespan or the completing time of jobs to be minimized. In order to solve this problem, in this paper, the Random-Elitist Genetic Algorithm (REGA) is presented in this regard. Observing the performance and the efficiency of this algorithm, we code it by the VBA and compare with the other results. We first test the performance of different crossover operators for our algorithm. Next, using a specific example, we examine the performance of our algorithm. The results indicated that due to very good searching; this algorithm has the good performance in finding the optimal solution and reaching the optimum solution in a very short time.
M. H. Kamfiroozi; A. Bonyadi Naeini
Volume 3, Issue 3 , September 2014, , Pages 13-23
Abstract
An enterprise resource planning (ERP) software can help organizations and firms in their activities like: production planning, purchase, human resource, finance, sales, inventory control and etc. Selection of an ERP is mentioned as a multi-criteria decision making (MCDM) problem. However, several MCDM-models ...
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An enterprise resource planning (ERP) software can help organizations and firms in their activities like: production planning, purchase, human resource, finance, sales, inventory control and etc. Selection of an ERP is mentioned as a multi-criteria decision making (MCDM) problem. However, several MCDM-models are proposed to solve this, but many of them didn't consider uncertainty as an effective environmental factor. In this paper, a new model has designed which used three-parameter interval grey numbers concept that is derived from Grey-theory. These numbers can help for reducing the uncertainty of data. Besides, a combination model for weighting has planned by implementing AHP and Entropy methods that are used in order to reduce uncertainty. And last, a decision making method (Three-parameter grey interval incidence degree method) is used for ranking process. There is a case study at the end of this paper that shows how this model works.
