INTERNATIONAL JOURNAL OF INDUSTRIAL MATHEMATICS
Year:2014 | Volume:6 | Issue:2|Papers Count:10

For better guiding a system, senior managers should have accurate information. Using Data Envelopment analysis (DEA) help managers in this objective. Thus, many investigations have been made in order to find the most productive scale size (MPSS) for the evaluating decision making units (DMUs). In this paper we consider this case where there exist subsets of input and output variables to be integer valued. We use data envelopment analysis (DEA) technique, which is a mathematical programming for efficiency evaluation and target setting for a set of DMUs, and develop a model with which the desired MPSS point can be found. The applicability of developed model is illustrated in the context of the analysis to show the validity of the proposed model.

Recently, Cho et al. [Y. J. Cho, R. Saadati, S. H. Wang, Common fixed point theorems on generalized distance in ordered cone metric spaces, Comput. Math. Appl. 61 (2011) 1254-1260] defined the concept of the c-distance in a cone metric space and proved some fixed point theorems on c-distance. In this paper, we prove some new fixed point and common fixed point theorems by using the distance in ordered cone metric spaces.

In this paper a modification of He's variational iteration method (VIM) has been employed to solve Duffing and Riccati equations. Sometimes, it is not easy or even impossible, to obtain the first few iterations of VIM, therefore, we suggest to approximate the integrand by using suitable expansions such as Taylor or Chebyshev expansions.

In this paper, we present a fourth order method for computing simple roots of nonlinear equations by using suitable Taylor and weight function approximation. The method is based on Weerakoon-Fernando method [S. Weerakoon, G.I. Fernando, A variant of Newton's method with third-order convergence, Appl. Math. Lett. 17 (2000) 87-93]. The method is optimal, as it needs three evaluations per iterate, namely one evaluation of function and two evaluations of first derivative. So, Kung and Traub's conjecture is fulfilled. We also perform some numerical tests that confirm the theoretical results and allow us to compare the proposed method with some existing methods of the same type.

In this paper, the Picard method is proposed to solve the Bernoulli equation with fuzzy initial condition under generalized H-differentiability. The existence and uniqueness of the solution and convergence of the proposed method are proved in details. Finally an example shows the accuracy of this method.

This paper concerns the problem of robust stabilization of uncertain fractional-order non-autonomous systems. In this regard, a single input active control approach is proposed for control and stabilization of three-dimensional uncertain fractional-order systems. The robust controller is designed on the basis of fractional Lyapunov stability theory. Furthermore, the effects of model uncertainties are fully taken into account. Also, the robust stability and access to the equilibrium point of the control scheme are analytically proved. Moreover, fast response and easy realization in real world applications are some special features of the suggested method. Finally, as a numerical simulation, control and stabilization of three-dimensional uncertain fractional-order Chen system is provided to illustrate the usefulness and applicability of the proposed approach in practice. It is worth to notice that the proposed active control approach can be employed for robust stabilization of a large class of three-dimensional uncertain nonlinear fractional-order non autonomous dynamical systems.

The hybrid fuzzy differential equations have a wide range of applications in science and engineering. We consider the problem of finding their numerical solutions by using a novel hybrid method based on fuzzy neural network. Here neural network is considered as a part of large field called neural computing or soft computing. The proposed algorithm is illustrated by numerical examples and the results obtained using the scheme presented here agree well with the analytical solutions.

This research has studied and ranked the service quality and its relation with customers' satisfaction in a bank in Iran. In the theoretical principles section, the concepts and definitions related to services, satisfaction, banking and research background have been studied. The statistical community of the study was all the bank customers that have referred to the bankand have had interest-free loans savings accounts or current accounts. The study statistical sample was calculated using the formula; then a questionnaire was designed and distributed among sample members and finally, the research hypotheses were examined using collected data. Pearson correlation coefficient test was used to test the first hypothesis and specifically related hypotheses. Also, the Friedman ranking test was used to test the second hypothesis. The first hypothesis test results showed that there is a positive and significant relationship between service quality and customers' satisfaction. The second hypothesis test results also showed that there are significant differences among the priorities of the constituent elements of service quality.

Data Envelopment Analysis (DEA) is an efficiency measurement tool for evaluation of similar Decision Making Units (DMUs). In DEA, weights are assigned to inputs and outputs and the absolute efficiency score is obtained by the ratio of weighted sum of outputs to weighted sum of inputs. In traditional DEA models, this measure is also equivalent with relative efficiency score which evaluates DMUs in compare with the most efficient DMU. Recently network DEA models are appeared in the literature, which try to assess DMUs regarding their internal production divisions and intermediate products. In this paper we compare absolute and relative efficiency scores in network framework. Since in network DEA models, an efficient DMU does not exist necessarily, the relative efficiency model helps us to have at least one efficient DMU in our assessments.