Journal of Operational Research in its Applications
Year:2012 | Volume:9 | Issue:1 (32)|Papers Count:8

The present study aims at determining a proper decision making model for investment. In this regard, the effective criteria for evaluating the performance of mutual funds are extracted through reviewing research literature. Afterwards, the importance of each criterion (sharp, trainer, Jensen, Sortino) will be assessed through using the Shannon entropy. The study sample includes eight mutual funds. Thus, given the small sample size and incomplete information, concept of grey systems theory and grey relational grade is used for ranking the sample. For this purpose, the actual data, in the period of 2008-2010 is used. After ranking, it came out that “Melli bank”, “Pouya “and “Sahm Ashna” mutual funds had the best performance in the above-mentioned period. Finally, investment ratio in each fund has been determined through offering grey and integer linear programming.

Data envelopment analysis (DEA) has been a very popular method for measuring and benchmarking relative efficiency of peer decision making units (DMUs) with multiple input and outputs. Traditional data envelopment analysis (DEA) models require crisp input and output data. In real world situations, however, crisp input and output data may not always be available, especially when a set of decision-making units (DMUs) contains missing data, judgment data, or predictive data. In this paper, a new model of Data Envelopment Analysis is provided to enable the user to decide the unit performance with regard to fuzziness data. The new fuzzy DEA models are formulated as LP models without the need of making any assumptions and too much computational effort. In addition, this paper, an analytical fuzzy ranking approach is developed to compare and rank the fuzzy efficiencies of the DMUs.

Pipeline as a safe and economic way, play an important role in the oil transportation. In this system, various type of products are injected into the pipeline sequentially without any physical separation, and on the other side, at the distribution centers, the products are received and depot in the corresponding tanks. Scheduling of oil transportation operations in a given time horizon is an managerial task that aim to optimize the process of transferring products to the distribution centers and deliver to the customers while satisfying daily demand. In the real life, there are various factors such as weather conditions, social and political events that may change the daily demand in the distribution centers and as a result the preliminary schedule must be updated. Thus, a stochastic model presented and the model is evaluated with different methods, we are concluded that it can be used as a tool for efficient and effective decisions.

In today’s competitive world, many manufacturing and service companies, have been forced to proceed new management approaches. Among these approaches, can be noted new methods of performance evaluation that have an important role in improvement of organization performance. Balanced scorecard is one of the recent management innovations that evaluated organization from the four major management perspectives with the aim of providing a comprehensive view of business for executives. But a key component to any BSC is the baseline or benchmark against which performance is measured. Without a standard or a baseline, evaluation is impossible. However, standards are hard to determine and can be misleading. To solve this problem, integrated DEA and BSC model is proposed. Data envelopment analysis model is method based on mathematical programming and a non-parametric approach that used in evaluating the relative efficiency of decision making units with multiple same inputs and outputs. Since DEA is based on relative analysis, the decision unites evaluated against each other; thus by combining the BSC with DEA we overcome one of the major obstacles of BSC, namely, the need to determine standards. In this paper a new model of balanced DEA-BSC is offered. The main advantages of the proposed model are providing a comprehensive insight of business for executives, a balanced assessment based on all BSC Indicators, and creation balance between them, linearity and flexibility of model and high separation power. Finally, the experience of using the proposed model in performance evaluation of Yazd Tile and Ceramic Companies is presented.

This research is proposed and accomplished to compare AHP and Fuzzy AHP, in consumers’ believes assessment and to rank the criteria in choice a refrigerator brand. The questions that would answer in this research are: What criteria are noticed to buy household appliance? Which ranking do these criteria have? Do the consumers differ between the quantitative and qualitative criteria, for choose a brand? Does decision making based on definite criteria, have a significant difference from decision making based on fuzzy criteria? In this research, pure data analyzed by three methods: 2-level classic AHP, 2-level fuzzy AHP and 3-level fuzzy AHP by means of expert choice software, and in ever methods, nearest ranks observed in ranking by 3-level fuzzy AHP, and then 2-level fuzzy AHP.

Most important factor for obtaining optimal organizational productivity is efficient human resource. In competing environment and as human resource development methods are expanding, so organizations are trying to maintain their capable staff and empower them to show high performance in their work. South-Pars region as energy capital, national development pole or axis of country development, needs motivated and capable staff and keeping these employees and productive utilization of them are very important. A factor that decreases staff productivity and increases probability of incidents and direct and indirect costs is stress and mental pressure of employees of that region. Industrial management without considering “human resource health” will be faced to costs and damages that might not be recovered by technology enhancement or process improvement. After studying researches, related texts and interview with employees of South-Pars gas complex, 31 organizational stressful factors have been recognized. For preliminary filter and specifying most important organizational stressful factors, many interviews with experienced employees, region experts and supervisors was done and 12 main organizational stressful factors have been identified. These 12 factors categorized into environmental and managerial factors so people could say their opinions clearly. These factors have been ranked by group fuzzy AHP and coding of this method has done by MATLAB program. Accepted questionnaires (according to inconsistency rate) by help of this code will be transformed to mixed matrix. Scores of people in the form of geometric average are in mixed matrix. Ranking was done among different refineries of gas complex. Inaccurate evaluation of staff, prejudice in remunerations, incorrect human resource movement to new refineries and danger of poisonous and chemical substances were introduced as high stressful factors. And at the end, correlation of employees’ points of view in 5 refineries was investigated and gained result was that points of view were correlated except in one refinery.

Data envelopment analysis (DEA) does not provide more information about the efficient decision making units (DMUs). A method to rank efficient DMUs is common set of weights (CSW). This research proposes some simple methods to find common set of weights CSW for the performance indices of DEA efficient DMUs. These methods use the results of the standard DEA models to determine the CSW. Unlike the existing methods, the resulted CSW is determined without deleting or rounding the weights and put all weights in computation.

The usual procedure when employing a T2 control chart for multivariate process monitoring is to take samples of fixed size n0 every h0 hours from the process. Recent studies have shown that using variable parameters (VP) schemes results in charts with more statistical power when detecting small to moderate shifts in the process mean vector. In this paper, the VPT2 control chart for monitoring the process mean vector is economically designed. The cost model proposed by Lorenzen and Vance is used here and is minimized through a genetic algorithm (GA) approach.