JOURNAL OF NEW RESEARCHES IN MATHEMATICS
Year:2016 | Volume:2 | Issue:5|Papers Count:8

The first objective in any financial organization is to improve performance, and performance evaluation also is one of the best ways to advance operations in organizations. By utilizing different methods of performance evaluation, organizations can evaluate the effectiveness and efficiency of processes that are in accord with strategic objectives. In addition, the performance evaluation instruments can help organizations with resource allocation and appropriate distribution of these resources. So far, many performance evaluation methods have been introduced which among them, traditional approaches only focus on the financial aspects and do not concern the non-financial. This article primarily concerns the linking of strategy maps and performance indicators that provides a structure of performance evaluation for the Saderat Bank of Tehran; and in the next step evaluates efficiency of bank branches by using Data Envelopment Analysis method.

According to the growing trend of IT-based systems, implementation of computerized maintenance management system (CMMS) in Iran’s power industry can dramatically help in optimized management of maintenance activities, and thereby, reducing equipment failures, increasing reliability, increasing product stability and, above all, increasing efficiency and productivity of the employees of this industry. The aim of this article was to examine the impact of computerizing the maintenance and repair process on efficiency of the staff of Isfahan south power plant, measure the efficiency of staff, identification of efficient and inefficient staff, rating of efficient staff, and finally, to investigate and compare the effect of factors influencing their efficiency to increase the organization productivity with job satisfaction approach. To do this, after identifying factors contributing to job satisfaction of employees through questionnaires distributed among 40 employees associated with CMMS, a DEA including four job satisfaction inputs and outputs was defined. With solving the model by CCR method, the efficient and inefficient employees were determined. The results of sensitivity analysis on model inputs determined the effect of each input on the output in accordance with the following ranking: 1. Workplace safety and ergonomics2. Computerizing maintenance management system (CMMS) 3. Training 4. Job nature The results indicated that the CMMS has the second ranking among other influential factors. Finally, the efficient personnel were ranked by Anderson Peterson method.

Introduction: Data envelopment analysis (DEA) is a data-oriented method for measuring and benchmarking the relative efficiency of peer decision making units (DMUs) with multiple inputs and multiple outputs. DEA was initiated in 1978 when Charnes, Cooper and Rhodes (CCR) demonstrated how to change a fractional linear measure of efficiency into a linear programming format. This non-parametric approach solves an LP formulation per DMU to obtain an aggregate efficiency score to each DMU. A new variety of efficiency as partial efficiency has been faced in this paper.Aim: The current paper studies the problem of partial efficiency in DEA. By using a DEA model, the paper determines a sharing matrix of inputs to optimize the aggregate efficiency of DMU under consideration.Material and methods: Toward this end, we have used the well-known non-parametric technique DEA.   Results: In this paper, we introduced a DEA model to (i) maximize the aggregate efficiency score and (ii) to determine the partial efficiency of each output. Conclusion: Traditional DEA models give an overall efficiency score to each operational unit based on the observed inputs and outputs. In the current study, new efficiency indexes are introduced. These partial indexes are referred to as partial efficiency of outputs. The paper gives the best resource allocation to maximize the aggregate efficiency of DMUs.

Comprehensive methods must be used for portfolio optimization. For this purpose, financial data of stock companies, inputs and outputs variable, the risk measure and investor’s preferences must be considered. By considering these items, we propose a method for portfolio optimization. In this paper, we used financial data of companies for screening the stock companies. We used Conditional Value at Risk (CVaR) as a risk measure, because of its advantages. Data Envelopment Analysis (DEA) can be used to calculate the efficiency of stock companies. Conventional DEA models assume non-negative data. However, many of these data take the negative value, therefore we propose the MeanSharp-bCVaR (MShbCV) model and the Multi Objective MeanSharp-bCVaR (MOMShbCV) model base on Range Directional Measure (RDM) that can take positive and negative values. By using Multi Objective Decision Making (MODM) model, investors can allocate their capital to the stocks of portfolio as they like. Finally, a numerical example of the purposed method is applied to Iran’s financial market.

Data Envelopment Analysis (DEA) is a widely used technique for measuring the relative efficiencies of homogenous Decision Making Units (DMUs) with multiple inputs and multiple outputs. These factors may be evaluated in fuzzy or stochastic environment. Hence, the classic structures of DEA model may be changed where in two fold fuzzy stochastic environment. For instances, linearity, feasibility and normal domain of efficiency scores (input orientation) between zero and one are some of these properties. In this paper, a new approach based on alpha cuts is proposed for evaluating decision making units with fuzzy stochastics inputs and outputs. The proposed approach modifies these weaknesses to solve DEA models with fuzzy stochastic parameters. A numerical example is given to illustrate the features and the applicability of the proposed model.

Let G be a simple graph with vertex set {n1, n2, … , nn}. The common neighborhood graph of G, denoted by con (G), is a graph with vertex set {n1, n2, … , nn}, in which two vertices are adjacent if and only if they have at least one common neighbor in the graph G. In this paper, we compute the common neighborhood of some composite graphs. In continue, we investigate the relation between hamiltonicity of graph G and con (G). Also, we obtain a lower bound for the clique number of con (G) in terms of clique number of graph G. Finally we state that the total chromatic number of G is bounded by chromatic number of con (T(G)).

The present paper, titled “optimizing the time of preparation, taking into account the timing of   repair and maintenance using non-linear modeling”, has been implemented with the aim of designing and presenting a mathematical model to get the best sequence of operations leading to minimum the total time of production. The main research question is related to the reduction of time and production costs following the implementation of the presented model.The method of research’s data and information collection, have been survey and study and library resources, referring to the documentations of repair, maintenance and production segments in the company and expert managers in the areas of planning, engineering production and … Following, the model taking into account the constraints of cost and time, as well as the limitations of the production system is presented. LINGO software is used to solve the models and model outputs, will provide the local solutions that would show the best sequence. And finally it can be extended the model to other industrial units with only smart alternations and present the best operational sequence related to multifunctional machines.

Congestion is one of the main issues in data envelopment analyses which have particular importance. Recently researches about congestion, whether in economic articles or in Operations Research articles in had grown increasingly. Congestion is a wasteful stage of the production process where outputs are reduced due to excessive amount of inputs. In economics, congestion is very important because elimination of it results in decrease in costs as well as increase in outputs. Therefore the benefits of recognition of density and decreasing of it are high. In this paper, we will be introduced a method for definition and calculation of congestion degree under weak disposability of desirable and undesirable outputs in a Two-phase Network. And we will present a model for definition and calculation of congestion value considering desirable and undesirable final outputs.