INTERNATIONAL JOURNAL OF INDUSTRIAL MATHEMATICS
Year:2011 | Volume:3 | Issue:3|Papers Count:7

In this paper, a nonlinear Fokker-Planck equation is solved by using the modified Ado-mian decomposition method (MADM), variational iteration method (VIM) and homotopy analysis method (HAM). For each method, the approximate solution of this equation is calculated in the form of the series which its components are computed by a recursive rela- tion. In some theorems, the uniqueness of the solution (if it exists) and the convergence of the proposed methods are proved. Finally, a numerical example is solved to demonstrate the accuracy of the mentioned methods.

In this paper, He’s homotopy perturbation method is applied to solve two-dimensional linear and nonlinear Volterra integral equations. Then homotopy perturbation method (HPM) is compared with the differential transform method (DTM) for solving two dimen-sional integral equations. We also give some examples to demonstrate the accuracy of the method. From the computational view point, the homotopy perturbation method is more efficient and easy to use.

In this article a successive approximations method is used to solve nonlinear fuzzy Volterra integral equations along with representing its error. Then using quadrature rules we approximate the present integrals in the sequence of successive approximations and we obtain the numerical solution we have tended to.

One of the main problems in Data Envelopment Analysis (DEA) is ranking Decision Making Units (DMUs). There exist many different DEA models. These models often do not have any theoretical problems dealing with most data. However, because each of these models considers a certain theory for ranking, they may give different ranks. So, often in practice, choosing a ranking model, the results of which the Decision Maker (DM) would be able to trust is an important issue. In this article, ranking is done by proposing a method in which the ranks of different ranking models are used, each of which is important and significant. This method is based on the voting system. In voting systems, one candidate may receive different votes in different ranking places. The total score of each candidate is the weighted sum of the votes that the candidate receives in different places. The candidate that has the highest total score has the best rank. In this paper, we consider the various ranking models as voters which can rank DMUs from the top to the end and DMUs as candidates try to obtain a full rank from their votes.

Nowadays, improving the competitive condition of organizations greatly depends upon the process of outsourcing. Raw materials, products, services, or some parts of the orga- nization activities can be outsourced. Thus, the process of outsourcing is regarded as a strategic decision. At the same time, the first step after making decision on outsourcing is selecting the appropriate supplier in the given area. Due to the importance of this issue, so far many extensive studies have been conducted on offering appropriate solutions to the problem of supplier selection. In this paper, a hybrid system consisting of Data En-velopment Analysis (DEA) and group decision making based on fuzzy models is proposed for solving the problem of supplier selection. In this hybrid system, first the weights of the criteria are obtained from every decision maker as fuzzy numbers and group decision making, and after being integrated, they are incorporated into the DEA model using the concept of intersection in fuzzy numbers. Then, DEA model is solved through Assurance Region (AR) method in order to select the best supplier.

In this paper, the propagation of electro-magneto-thermoelastic disturbances produced by thermal shock in a perfectly-conducting half-space is studied based on Green and Naghdi (G-N) theory. Normal mode analysis is used to obtain the exact expressions of temperature, displacement and stresses. Comparisons are made with the results predicted by G-N theory of type II and type III in the presence and absence of the magnetic field.

In this paper, the fuzzy solution of non-linear fuzzy Volterra integro-differential equation (NFIDE) is approximated. To do this, we define a sequence of fuzzy functions which approximate the fuzzy solution of this type of equations and finally, we estimate upper bound of the error.