INTERNATIONAL JOURNAL OF INDUSTRIAL MATHEMATICS
Year:2014 | Volume:6 | Issue:3|Papers Count:9

In this paper, we investigate the general fuzzy linear system of equations. The main aim of this paper is based on the embedding approach. We find the necessary and sufficient conditions for the existence of fuzzy solution of the mentioned systems. Finally, Numerical examples are presented to more illustration of the proposed model.

Supplier selection is a multi-Criteria problem. This study proposes a hybrid model for supporting the suppliers’ selection and ranking. This research is a two-stage model designed to fully rank the suppliers where each supplier has multiple Inputs and Outputs. First, the supplier evaluation problem is formulated by Data Envelopment Analysis (DEA), since the regarded decision deals with uncertainly and ambiguity of data as well as experts and manager linguistic judgment the proposed model is equipped with Fuzzy approach, then in this research we use of Fuzzy DEA for first stage. In the second stage, efficient suppliers are ranked with Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) model. Fuzzy DEA PROMETH EE ranking does not replace the DEA classification model; rather it furthers the analysis by providing full ranking in DEA context for efficient suppliers.

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In this paper, the variational iteration method for solving nth-order fuzzy integro differential equations (nth-FIDE) is proposed. In fact the problem is changed to the system of ordinary fuzzy integro-differential equations and then fuzzy solution of nth-FIDE is obtained. Some examples show the efficiency of the proposed method.

Mathematical modeling of supply chain operations has proven to be one of the most complex tasks in the field of operations management and operations research. Despite the abundance of several modeling proposals in the literature; for vast majority of them, no effective universal application is conceived. This issue renders the proposed mathematical models inapplicable due largely to the fact that real-life supply chain problems are set forth in restrained terms or represented less strikingly than they would bear out. This paper is triggered to bridge this gap by proposing a universal mixed integer linear programming (MILP) framework which to large extent simulates many realistic considerations in vehicle routing scheduling problems in cross-docking systems which might have separately been attempted by other researchers. The developed model is pioneer in excogitating the vehicle routing scheduling problem with the following assumptions: a) multiple products are transported between pick-up and delivery nodes, b) delivery time-intervals are imposed on each delivery node, c) multiple types of vehicles operate in the system, d) capacity constraints exists for each vehicle type, and finally e) vehicles arrives simultaneously at cross-docking location. Moreover, to solve the model a hybrid solution methodology is presented by combining fuzzy possibilistic programming and stochastic programming. Finally, in order to demonstrate the accuracy and efficiency of the proposed model, an extensive sensitivity analysis is performed to scrutinize its parameters’ demeanors.

In this paper, the Ritz-Galerkin method in Bernstein polynomial basis is applied for solving the nonlinear problem of the magnetohydrodynamic (MHD) flow of third grade fluid between the two plates. The properties of the Bernstein polynomials together with the Ritz-Galerkin method are used to reduce the solution of the MHD Couette flow of non-Newtonian fluid in a porous medium to the solution of algebraic equations.

This paper proposes improvements and revisions to a recent approach in a voting system, and provides an effective approach with a stronger discriminate power. For this purpose, the advantage of a linear transformation is utilized to redefine a previously used concept of virtual worst candidate, by incorporating the existing weight restrictions. Then, the best score of this virtual candidate is used as a lower bound for the scores of the candidates in the models. It is shown that the proposed approach overcomes some drawbacks in the existing models. The approach determines interval efficiencies which can be used in ranking the candidates. Numerical examples illustrate some advantages of the proposed approach.

Making capital and investment is the main driving forces of economic development. Based on the investment sensitivity to the changes of some of macro-economic variables and risk and uncertainty, the present study evaluated the effective factors on investment in private sector in Iran during 1980-2007. At first, the uncertainty variables of real informal exchange rate, nominal interest rate and inflation rate were calculated by GARCH model. Then, by ARDL model, the effect of calculated uncertainty indices besides the main values of the variables and some of the other control variables on investment in private sector in Iran was investigated. The estimation results showed the negative uncertainty effect of the real exchange rate, inflation rate and nominal interest rate on investment in private sector in short-term and long-term. Also, the gross domestic production and inflation rate had significant and positive and negative effect, respectively on investment in private sector in Iran. In this model, there was no relationship between the size of civil expenditures of the government and real exchange rate with the private sector investment in our country. The error correction term coefficient showed that moderation to balance is done during more than 3 years.