فصلنامه مهندسی تصمیم
پیاپی 1 (زمستان 1393)

AlthoughStrengths, Weaknesses, Opportunities and Threats (SWOT) analysis is a suitable tool for identifying effective factors in order to determine the strategies for an organization, but this analysis cannot take into account the importance or preference of the factors. Consequently, SWOT is unable to determine the most appropriate strategy for the organization. Because the factors in SWOT analysis are not independent, the combination of SWOT with the methods such as AHP and TOPSIS cannot solve the problem. Using the ANP which can consider the dependencies within the factors, along with SWOT analysis is able to solve the problem of dependencies, but in real world, there are some other limitations such as budget or labor hours which need to be considered in the problem. Combined ANP and SWOT analysis take into account these mentioned limitations. In this paper, the combination of ANP along with goal programming approach is proposed with SWOT analysis in order to remove these drawbacks. The proposed approach not only considers the real world limitations but also with its distance function, is able to choose the most appropriate alternative. To validate the proposed approach, the model was applied for textile industry in Turkey and Iran. The data for the Turkey, taken from the research which have been done by Yuksel and Dagdeviren. The results show the two countries, apply the same strategy for the textile industry. However, the comparison shows the Iranian experts has the most consistencies in their judgments.

Investment portfolio selection as one of the most important issues raised in the area of financial engineering Mean-Variance model revolutionized portfolio selection problems. Although this model has unique theoretical properties, its weakness prevents the use of this model in practice. Recently many studies on improving the performance of the model have been done.
In this thesis, a multi-objective portfolio selection model is considered including the uncertainty data. In particular, the aim of this thesis presents a Robust - Fuzzy Multi-objective model for portfolio selection.
After presenting Multi- objective optimization approach, robust optimization approach and Fuzzy optimization approach, Fuzzy- Robust Multi-Objective model for portfolio selection is expressed. Finally, using real data to solve the proposed model

Todays, analysis of chaotic systems is one of the crucial challenges of researchers in machine learning field. The ability of classification and extracting implicit knowledge of such kind of data enables us to provide powerful prediction systems in various fields of engineering and economics.
So far, various methods such as evolutionary algorithms, neural networks and etc. have been employed to process this type of data.However, an ideal and universal solution to that has not been reached. In these circumstances, addressing new algorithms that can help in this direction seems necessary. For this purpose, we present a new computational algorithm based brain emotional learning in this paper. This method used the reinforcement learning to govern dynamic data and find the rules and extract knowledge in chaotic systems. To do so, we apply our algorithm for classification of brain signals (one of chaotic systems).At the end, we prove the efficiency by comparing the results of the proposed algorithm with two other famous one.

Achieving top and sustainable economic growth has always been desired in economic plans of countries. Proving the existence of positive relationship between financial market development and economic growth has made researchers study effective factors on growth and developing financial market. One of the most effective factors on the countries financial development is inflation.
Monetary and financial markets and their development are discussed to be a fundamental base for development and economic growth. In developed countries, these markets are extended. In developing countries, the expansion of these markets is in attention and considered as a target. Achieve this goal, means to expand the performance of financial markets, and requires sufficient information about the factors that affect these markets. Inflation is one of the most important factors can affected on development the financial markets. In addition to impact of inflation on financial market development, it can affect on optimal allocation resources. Therefore, in order to achieve the development of financial markets the inflation rate must be carefully guided.
The system based on market economy in macro level rests on quad markets. These markets include: goods, work, monetary and capital markets. Monetary and capital markets they are both related to financial sector. Financial sector the second aspect of the economy that actually complements real sector of the economy. Optimal functioning of the economic system in society depends on the existence complements, powerful and monitored in both natural and efficient financial sector. The combination of these sector activities is necessary and sufficient for desirable economic system.
In this paper, we use the ANP method to explore this topic that fits with the existing monetary and financial institutions, which sector is more appropriate for investment and targeted liquidity existing in society, in order to reduce inflation and stimulate growth in the industry. The results of both methods revealed the stock exchange is the best financial and investment institution in order to reduce the inflation that caused by the high liquidity of the present.

Now days, the use of information systems is a necessity in organizations. Enterprise resource planning system (ERP) is one of the important applications of information technology, especially in the banking industry in our country. There are a lot of providers of ERP software package inside and out. Therefore, it is so important to select suitable ones which cover all needs and aspects of our organization. To solve this problem, we need to build a complete network of all factors involved in the decision and we also need right tools to identify factors into the network. We have used Analytic Network Process (ANP) to make decision making network based on the research findings and innovations and we also have used Balanced Score card to identify effective factors .we have connected the two method together by using questionnaires to the 45experts and professionals in banking system and the 25implementing experts of this software package in Iranian companies. We have applied SPSS and Super Decision software’s to solve proposed model and make valid research results. As a result, an ERP software package of SAP Company is proposed with 0.375 score as the most appropriate one rather than Mysis and Douran for Bank.

Nowadays, businesses operate in an environment that change is an integral part of it. Organizations attempt to find ways to skip from uncertainty and reach to circumstances in which they can anticipate the future and prepare themselves for it. Iranian organizations are not exceptionary and sooner or later change fads will surround them. Dynamic capability is a new approach in this field. The orientation of dynamic capabilities is to know how to distinguish opportunities and reconfigure organization accordingly. On the other hand, the importance of innovation in progressing in the dynamic environment cannot be denied. In this research, we attempt to find how dynamic capabilities affect innovation capabilities. For that we have presented a mixed model and during the research tested it. A sample of 200 people from 15 companies, all of which are active in food industry, is selected. SPSS and LISREL have been used to calculate the data derived.