یکی از چالش‌های عمده ارزیابی عملکرد در سازمان‌ها و کلیه سیستم‌ها، غیرمنطقی بودن و دقیق نبودن روش‌ها و معیارهای بکار گرفته شده است. روش‌های سنتی ارزیابی عملکرد عمدتا یک سطحی بوده، لذا فاقد توان لازم بمنظور ارائه بازخورد کافی جهت شناسایی واحدهای ناکارا هستند. تحلیل پوششی داده‌ها، یک تکنیک برنامه‌ریزی ریاضی است که کارایی نسبی چندین واحد تصمیم‌گیرنده را بر مبنای ورودی‌ها و خروجی‌های مشاهده شده که ممکن است با انواع مقیاس‌های مختلف بیان شوند، محاسبه می‌کند. در عمل، بسیاری از واحدهای تصمیم‌گیری در درون خود به بخش‌های کوچک‌تری تقسیم می‌شوند و با مدل‌های استاندارد تحلیل پوششی داده‌ها که سازمان را به صورت یک بخش کلی در نظر می‌گیرند، نتایج منطقی حاصل نمی‌شود. بنابراین لازم است از مدل‌هایی همچون مدل DEA دومرحله‌ای متناسب با چنین شرایطی برای ارزیابی دقیق‌تر واحدهای تحت بررسی استفاده شود. همچنین در شرایطی که تعداد زیادی ورودی و خروجی وجود داشته باشد، این روش چندان کارآمد نمی‌باشد و تعداد زیادی از واحدها را کارا اعلام می‌کند لذا برای رفع این مشکل تحقیق حاضر با استفاده از روش PROMETHEE ، ورودی‌ها و خروجی‌ها رتبه‌بندی می‌کند، سپس با مهم‌ترین آنها کار ارزیابی ادامه خواهد یافت. از آنجایی که همواره اطلاعات در دسترس کامل و دقیق نیستند این مهم در فضای خاکستری انجام خواهد شد. یافته‌های به دست آمده نشان‌دهنده کاهش چشمگیر واحدهای شناسایی شده کاراست که در نتیجه بهبود قدرت تمایز روش DEA را نشان می‌دهد. در کنار این، استفاده از محیط عدم اطمینان به ارزیابی‌ها و برآوردهای دقیق‌تر نسبت به مدل‌های قطعی انجامیده است. پرونده مقاله

Abstract: One of basic principle of any organization is to assure about obtained figures from measuring products. If the measured data was not trusted, will be lead to a wrong decisions regarding the approval or rejection of products and obviously the cost would be great. First cases in measurement systems analysis which crossing minds are criteria for approval or rejection any measurement system using its obtained results. It seems that comparing and ranking different measurement systems have an important role in future of any organization, when every system is evaluated by common criteria in measurement systems analysis. In this paper duo to ranking different measurement systems as an Alternative and average Attribute and calculated indices is considered as a bench mark in measurement systems analysis. For this purpose, a multiple criteria decision-making model, VIKOR method has been presented.in order to determine the Attribute weight we used AHP method, before VIKOR. پرونده مقاله

A supply chain is composed of a complex sequence of processing stages, ranging from raw materials supplies, parts manufacturing, components and end-products assembling, to the delivery of end products. In the context of supply chain management, supplier selection decision is considered one of the key issues faced by operations and purchasing managers to remain competitive. Therefore, requirements of engineers or customers may result in product configuration change with product life cycle. Effective management of product configuration can actually enhance productivity and customer satisfaction. This study proposes a two-phase model in the first phase of which an innovative design for new parts will be proposed by contradiction matrix, and translating contradictions into 39 engineering parameters of TRIZ , solving them by 40 innovative principals and by means of AHP fuzzy. In the second phase, an appropriate supplier for new product will be selected by value engineering and target costing. Finally, a case of clutch system in SUPCO is used to approve the applicability of the proposed approach. In this study, the best choice is the use of fuzzy AHP. After determining the total cost of the target product and initial screening of the suppliers based on that, the index values are calculated for each supplier according to the criteria of the organization. Thus, the best suppliers with the highest value to the organization have been selected. پرونده مقاله

The stock selection problem is one of the major issues in the investment industry, which is mainly solved by analyzing financial ratios. However, considering the complexity and imprecise patterns of the stock market, obvious and easy-to-understand investment rules, based on fundamental analysis, are difficult to obtain. Fundamental and technical analyses are two common methods for predicting the future behavior of the stock.Fundamental analysis focuses on the economic forces of supply and demand which cause stock prices change. On the other hand technical analysis examines historical data relating to changes in the price and trading volume by using graphs and indicators as a primary tool to predict future price movements. Therefore, in this paper, a model has been proposed for selection of the right portfolio in stock exchange. Financial industries ranking and companies ranking have been applied for selection of the right stock in this model. These rankings have been done through the PROMETHEE decision making method. Technical Analysis has been done for determining the right time to buy and sell the superior stocks. A survey has been done for determining the effective criteria over industry and company evaluation. The developed model has been applied in Tehran Stock Exchange (TSE) as a real case and a real problem has been solved. It is concluded that by using both Fundamental and Technical Analysis, an investor can get higher return on stocks instead of using just one individual analysis. In other words, while fundamental analysis distinguishes which stocks to buy, technical Analysis shows when to buy the superior stocks.Finally, some important and most commonly used indicators have been extracted. These indicators can be used by investors to consistently and correctly predict the future stocks prices. پرونده مقاله

In order to survive in today's competitive world, organizations are looking to increase their efficiency and effectiveness. Therefore, they should focus on inputs that are more important than the rest of the inputs in their success. This paper aimed at ranking 7Ms (Management, Man power, Marketing, Material, Machinery, Methods and Money) and their sub-criteria of production in Iran. By improving manufacturing processes, manufacturing organizations create and establish their added value. The Analytic Hierarchy Process (AHP) is a very popular method in decision making process, and its inner dependence extension is used for cases in which criteria or alternatives are not independent enough. In FAHP, each option severity is displayed by fuzzy numbers in relation to criteria. Therefore, a fuzzy judgment matrix is obtained. In this study, Fuzzy AHP tool has been used to rank these inputs. The results are compared with the ideal ranking results and are examined that how different they are. پرونده مقاله

In the process of investment decision making, next to financial indicators many other aspects of investment projects are increasingly often considered. This leads to the multi-criteria evaluation of a project. The advantage of multi-criteria methods is the ability to take into account all (not only financial) aspects of the attractiveness of an investment project. The selection of criteria of project assessment must take into account the specificity of organization that makes a decision. Along with traditional method this paper introduces new approach for risk assessment based on each criterion characterizing the investment project on hydrocarbon resources exploitation. پرونده مقاله

This paper processes a combined method, based on VIKOR and Data Envelopment Analysis (DEA) to select the units with most efficiency. We utilize the VIKOR as compromise solution method. This research is a two-stage model designed to fully rank the alternatives, where each alternative has multiple inputs and outputs. The problem involves BELIEF parameters in the solution procedure. First, the alternative evaluation problem is formulated by Data Envelopment Analysis (DEA) and in the second stage; we use the opinion of experts with belief parameter to be applied into a model of group Decision-Making (DM) called the aggregated fuzzy belief decision matrix. . In this method weight of efficiency witch obtained from VIKOR is multiply with weight of CCR model of data envelopment analysis. Finally, to illustrate the proposed method, an illustrative example is provided. پرونده مقاله

One of the most important activities in the management of input items of a company is focusing on the process of purchasing, supplier selection and allocating order to suppliers. Decisions about supplier selection due to simultaneously taking inconsistent and diverse issues into account in a wide range of strategic to operational factors, and from quantitative to qualitative criteria will be complex by nature. In order to select the best suppliers it is necessary to make a trade-off between these tangible and intangible factors some of which may conflict. When business volume discounts exist, this problem becomes more complicated. In this paper a multi-objective model for order allocation under volume discount conditions is presented. In this context, suppliers offer price discounts on total business volume. A solution methodology is presented to solve the multi-objective model, and the model is illustrated using a numerical example. Studying various combinations of constraints such as capacity, timely delivery, disadvantages and cost, taking into account quantity discounts, considering the weight of the suppliers in order allocation and integration of these cases with each other, have made the current research quite unique. پرونده مقاله